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HA<uAHB9OHBHHuHZDEJ1HHЋtHA<uA9O9w9} HxH`LLpLH8&urE1EEEEG@A A A @E<]D9uvDuAD;uRDH`A<L,tA <uI?E1IHHIHHE1HBHAHtH9t ,uHBHHHuEaI`H9HEHx1ҾHE!@Mt L$HE1H >HHt#H9t ,uH H >HHHuHH9}HIUEЈUHEIwN@(He[A\A]A^A_A< kIHt-MeL`I H@HXt؃AăuIHH@IEMtIDžADžIHtt IDžD9uUAGAD;uU}Hp1Q@IQMHxLHAyMOI @uхtQI @uU΍9t/11I @u 9tI9uAqd%Ht ̟eƎE9EDmEHEHEAD9mPDH`A<L$uI$(I$HI$PH)IT$ H6ID$HBHxIT$hHt ID$ HB I$I$@HtI$@uI|$|I|$8 DHtHߋGH_uXHuI$FI$I$`H9t,A$ ZI$ Ht I$HtLAD9mHt ̟Ď}t,HXHHHJMHUH;AFNO=JHhHxoIHHUHH&I1HH1ҾyIHHztH<uAHHMAIĸIniEfI$ID$HxHHHEHIHhHe[A\A]A^A_EHEHEpIuHp#}1T;f1"}1Ҿ#} aKIT$0It$ #}1kTpHwHthI$HHA$ H9HsHtu1H;HIHJH9HHHH|tH=I$@HtoH}tNH;EtHHI+$(H;MtMHH9UH9H;Ev1HMHEEfDHI+$(H}HUuHEEHHHHztH|HBHHBH;=MEfUu%}DuHWH%H8H7HuHH|HlHHuH#}pQ&iHUHEHMEHH E HHwʿ"}1lRSHu;t3Ht ˟HMHt [˟[Hw#}11HH(H<$t$?qHHT$1҅uH|$`H|$8HT$HH(DfDSHHwuCHWH?'}L DHHDH91H$HCH[ú#}h|"1H11HHH`@q?HSH HHT$H<$Ht$t ˟iH@q1uH\$Ht ˟=HH [@SHHWHwH?l*HC[ÐSH0HH<$Ht$HL$HT$t ˟侎H`Aq1euH\$ Ht ˟踾HH0[SHHOHWHwH?)HC [ÐHIH H1HHft( Ht Ht HH uHBH8 t!H8 tH8 t H8 uHHHH1HDÐHH+D DHH?HHHHHHHHH;DsHHDfH\$Hl$HLd$Ll$HHHIAH=@DtW1Ҿ@S)y-H$H$L$L$H1Ҿ`SHxHH`SH-CHCL%CD-CH$ BqDŽ$HDŽ$HD$xHD$pHD$hHD$`HD$XHD$PHD$HHD$@HD$8HD$0HD$(HD$ HD$HD$HD$GHDŽ$@BH$H$H$@SHH$H$(1H=Bt1Ҿ@S'V1Ҿ`SHhBF:ÐSHH?KDC  LO0EHsHC [AWHHAVAUATUSHhH7H|$ HD$(  HHHPHHD$` `HD$(HHHD$0  HH[HPHNHD$X `!HD$0HI I HHHPHHD$P `I MS HHsHPHfHD$H `9I MJ HHHPHHD$@ `I MA HHHPHHD$8 `]I Mp HH)HPHI `I Mf HHHPHI `I$ Il$ HHtgHpHt^H HsHHtL `uHLD$LL$LT$L$(HsHHlL$LT$LL$LD$HuL)HIIUIHIM)IMIWIHM)IMHD$8HPHHD$8H{M)IMHD$@HPHHD$@H M)IMHD$HHPHHD$HHM)IMHD$PHPHHD$PH1L+\$0IL\$0HD$XHPHHD$XHHD$(H)D$0Hd$0HD$0HD$(HD$`HPHHD$`H/HD$ H)D$(H|$(HD$(Hh[]A\A]A^A_@UAABHAWH@AVHAUHATHSHHHH)ĉ DH|$HHH}HHWHG  1EDž|tiE1E1DDAH ƍBHRIH@HHHHHP  E9Ј uDAZH@|HHHHEH8H@H@HddHH8H8HIHHP E1HPHzH6HP HAhHQH@HM]HXHEEHHLbH8E1H`!Mt DAI I$IHH`HXI\$$HHXHHuLEHUHuH}Dq;H]AHYHM `qH0H@|HT$HHBHJHS  H@!HHE1Mt{A_DI|HLHPHH HPLHHHHH+HPAHHH< H8DE DEH8H@HH8uDžLHdD EuDHEHHHt <B||HSHHHHL | HH4‹|HDžCHHH HEHH HMHIHHMHUHJ tHHlHPHHHH)H|$HH]IH=HPHHHH)H|$H]}HEELeDLpDžLa1HHHH]HCHHC HCHHEuȉz HeHE1҃v>HDкLI H9Nu fH9 ;uHAD9wHHHH =HH01HBHHH)H\$HHH( HDžAHEHHHD;EHH=tH=foHXI\$$HHHvHI|$Huypv(LEHUHuH}DqH4H]AHH`H0Ht$HHMHHBHFHBHFHEHBtHEDAIHUH ` H`Hq  HUHJ Ht HBHAHUHJHt HB HA HUHFH@ HB HVHEHB HUHB HtHPHU|H@H9`HFHBH`HkHH9[fKH%H)Lt$I-Hd gHHAHH;PuH`HsHAH;@H@H@HDHAHJ H@Ht HBHAHUHJHt HB HA HUHFH@ HB HVHEHB HUHB HHPHU1HHH}@sH}LEHUHuDq1H}H}}SpHH`HHFHBHFHBNH@H`;HnHPHHHH)H|$HH]IH?HPHS:u Ha-H$}1$;1HHpsD-`-EHIHPH@HHHH=rHCrH9HBHvHHpIIEHP1HHH)HT$H~8HI|$[$}1H1"11wfBHPHH@H@HwHJ9BHHPH@HGHHHq 0%}0LHMELHu1҉0L=OrL;EUIL,M9 IHt HIIMM.A Mf A IHt8HpHt/HfDHsHHt `uLRM$M)LHt&C1HpIHHЀ H9uL$I|$HIHxXLH8IE9UIuX%}1ҿ/H1ҿ Hq%}.HPHQ:u H]-H$}17$}1H1.Iw0%}1ҿ .H\$Ll$HLt$L|$IHl$Ld$H8 AIt)H\$Hl$Ld$Ll$ Lt$(L|$0H8fDHw Ht}1oHHtHHBLLDHHtHHjH+H@Hb1L`fHLLDTL9u:H,Dk Tu H^\-H0%}16Gf.AWAVAAUIATIUHSH(L@HHH=nHuEMuRt#HLDHu HN[-H0%}1o5릐UHAWE1AVAUATSHXMHUAHHuHB1HMEHH)HD$HHHEpHU5EoEL;eHUHM1EEL)Ju Hu HU-H011'E;Hu1ɺ 9X&}IHDžpX&}HxHEm&}PLHEH\m&}6HDX&}HH)H\$HHLHm&}H|Hٻ@IPIH0:u HT-HLI%}L1.H&}HE&}HE!}HEHHxH\!}iHD&}HH)H\$HHrH&}HDž&}LHDž &}HDž0!}H(LH&}IHIIT!}HJ HD&}HH)H\$HH'LH&}HHH!}HHٻfDUHAWAVIAUATSHHGhhdH(H@HhHpHXHUHHxaHHE1HEHRDžlHf8HEHUBHpL,IF0HL$ ʆMuMd$MLL&t㋵dHUBHHI~DKMD$(KIv0?u H(R-H8HpDDh$ lC%A9DBC uHUB tjHHUAt<1fA9v*IALJ4.%tIN$E1DžlE1H}t*HEIHPHB%A9DBBuEulHe[A\A]A^A_A_芸HII0&} IHxAH@I8{HxI>HzGH48HVfHRH ADF%BD FHpIЋGHpJDF uG tHH}HEI>HxHGDG u@WIGfHRH4D1DHD8HpHыGuDžlA$ jDE8Hu1ɺ LmA13HEX&}HEHE&}I|HIHuID$E1HH)H\$HHKtIIHuH1Iv>u H+O-H011 AUAATAU1SHHtHfD t1H[ HuH[]A\A]DDHu͐SHE1HH7LGHW(CHHHD$${HH[fUIIHAWEAVAUIATISHxL59aHEMLtSL;HrAL;Ps8 LHLxLpyLxLpujH[HuMItWIHUE1MLLHD$D<$HU1Ht HtHHJHeH[A\A]A^A_IL95i`thLHHHuHHULt$$E1MLL;d%uEIHUAHD$D<$MtM;Hr M;Pr&}111HEAL]LuLUD}HEd%HUHuH}LEhqHEA1d%u!dH<%d4%HHH]Hu HEHHPHHHH)H|$HH]IHRHPHHHH)H|$Hr}Ht H}L1HDA1cH(E1IH$D$ BAȄHH BAȄtwHHBAȄtbHLJHBAȄtIHHAAAȄt3IHHH%HHH1H1A@IuAȐDD$HE1LHD$H(Ð&H=}zÐ1E1HHЃHI xHLf.1E1HHЃHI x?w@t HHI HLHHHHHHHHGHtHIÿAH<@HHc4u@HuHHÀ9tHH;fDH;@HYHcH 4u@uHHÀ:HtHG;H\$Hl$HLl$Lt$ILd$H8@PIΉt&DD v:H HcHHBHHHIH\$Hl$Ld$ Ll$(Lt$0H8HHCHtApALDL@yHHCHcHCHHCHt$HHT$Ht$HzHT$랋HCDfDH@t(p t,~@t:@u1HDHH@uHHfHH{uoic]WQKE?9H(HH51HtHT$HH(fDfDUHAWIAVIAUIATISH8Hǁ dH%(HE1H9HHHH?HH9HEfDA$I@t.1LrHhA|$htLd$HBHz I HxWAIIqAIIpALIIVHL$HƉIHD$HPILt$H|$1@tgD-Ht$ LILt$ IHt$ LIIHD$ LHD$ƅrHfDATIUH1SHH$dH%(H$x1HH@HHH$@ID$H$+t(1H$xdH3%(HHĀ[]A\Ã$@tHt$1<t$HD HHHt<)uHFHD H$(HEH$0fH$hfH$PHEH$xHEM_fDLd$Ll$1H\$Hl$HXH9IIIH $sxA IAH$(HH$(HH$(sHH$(aH1H$(Q1H9H$(<1H9H$('1H9Y1H9H$(1H9H$(1H9"#t0tS fHH$(HH$(H$LzIH$H$(AItHVH$(ZH$(JH$(;AWIHAVAUATIUSH8HT$0dH%(H$(1HT$H|$$@t $uJHD$hHtNH@I$t AƄ$A@ID$8tSfL%HD$H8Hu=I$u$@HD$ tƄ$HD$ HD$h{A0H$HcHHL0<0@uHIM(I_L-M$;wQH٥ HcHH{Ht$HHt$HT$HL2A$@t BƄ%IDHHIHuAs7HI $H$(dH3%(|H8[]A\A]A^A_A$@HCtBƄ%fDLIDzSHc€eH$@ HD0HA}9BƄ%ITA}HCBƄ%zH{Ht$lHHt$HT$HLA}BƄ%A$@HD0HI!$I8Ht$HHt$HT$H1IaHH/VH\$Hl$HLd$Ll$HH$II1H@HHHHEBH=u0-=xL$@tƅH$HHDŽ$@HDŽ$0HE8HDŽ$(ILH$H$L$L$HĸH5CH=w=Jf fDAUATIUHSH(@HF8H L-r%tA}Ht$H7HIHtPB#I|HtH+utHtH9tAUHIlHuA$@u IT$81Ht+H([]A\A]HE8IA$IT$8t1Hu@ HU8t HuuHI+$HH([]A\A]=mHuHD$@tƅHD$HE8f.H\$Hl$HHHGhK@HcHHL4u @u)HHH\$Hl$HÐ*HufDfDUHH]LeLmLuL}HHUdH%(HE1HH8HuH@HH0HPH(H(H0uLt;t6DžLHUdH3%(LuPH]LeLmLuL}ÐH8H0@uLtH(H0orQfAUATIUHSH@u1HDHH锿@uHHf[HH_AWIAVAUMATUSHhtHh[]A\A]A^A_uHh[]A\A]A^A_LD$\׾HHt1MtLоH$UHLHL$HHƉHEH}D$(SLt$8LXHHD$8HD$LHD$)8IHD$8Ht$\LHD$ nHŋD$\uHL;d$ \$)1VHL$PLH\$)1Iĉ3HL$HLH\$)1IĉHL$@LHƉLHIH$HD$PH9sLd$ L;d$ nHD$HH9PHD$@HfHH\$XL1L覽1ҾL藽HLLt$8HD$HD$|AWAVIAUIATUSHHHt ̟OH1D%Hu"L@HAօuzH[HtqHHD$0HD$8H$HCHD$HHD$fD$HHD$ L)HD$(HHHHD$0tHHD$8rHt ̟ OHH[]A\A]A^A_DfDH\$Hl$HXHHHHtMHqfT$HH$HD$'}HD$HHD$ H)HHD$(@Յu HHH\$HHl$PHXfHt ̟LNÐUHSHH3-HtDHHHuH[ÐSHHt<H{HH{HtԉH{ˉHÉHdHuH=.Hw{t袉H=Ht;HHHHHHHHuHHH=UHtHHF衇H=:HuH=6艇H&HU1SH=t 52uk 5'u` 1zSH2H_=?t uG u=HuHH+HHuH[]H=H HĀH=H HĀAUATUHSHHtQE1E1fDLHEP~)H8t#HX@dH3%0HtHLH}IIhL9mwHEHx.HUHRHHHEHxH}HH[]A\A]fDAVIAUATUSLg MI\$ HtEH{ HtH{0HtfH覅HtHHCHk(8/tHuI\$0HH{ Ht}H{0HkfDMn0Mt\Im HH} HtH7Ht$1HHtsHA(HHufHH9uyIH}H7Ht$1HHt7HA(HHu*HH9uyHEH([]A\A]A^A_H(1[]A\A]A^A_H=SuyHHHHt$HxYtH;H7Ht@1HHt+[H=HyfDHB(HHuHH9uxHHB;4qHH:HHxOHdHdHHtV1=t 5Tu> 5Iu3HLHpH>={t "u( uH= H=HĀH=HQHĀH=H ?aaamain.f(/,1x,a,' Seasonal Adjustment Program',/, ' Version Number ',a,' Build ',a,/,' Execution began ',a)X-13ARIMA-SEATS1.126(A1,8X,A,T92,'PAGE',I4,', SERIES ',A)(A1,8X,A,12X,'PAGE',I4,', SERIES ',A).logUNKNOWN(/,a) Unable to open ('1')(A,'Log for ',a,' program (Version ',a,' Build ',a,') ',a)('(a,',i2,'a2,a)')*-*(///, ' Type of Series',6x,'Additional',19x,'Series title',/, ' Adjust. Ident.',6x,'Identifiers',/).gmtgraphical meta file Program error(s) halt execution for .spc Check error file .err Execution complete for .spc at (/, ' NOTE: Correct input errors in the order they are detected',/, ' since the first one or two may be responsible for',/, ' the others (especially if there are errors in the',/, ' SERIES or COMPOSITE spec).',/)(/,' NOTE: The diagnostic files produced by the -s ', 'option are stored in the',/, ' directory specified by the graphics (-g) option.')abend.f('sspans: ',a)failed(/,' Sliding spans analysis failed : check error file.')60('history: ',a)('historysa: ',a)(/,' History analysis failed : check error file.')('errorstop: yes')acf.f(/,' NOTE: Can''t calculate an ACF for a ', 'model with no variance')8(/,' Lag ',12I6)(' ACF ',12F6.2)(' SE ',12F6.2)(' Q ',12F6.2)(' DF ',12I6)(' P ',12F6.3)@p}??(5x,'No significant ',a,' Qs',/)Ljung-Box(5x,'Summary of Significant ',a,' Q:',/, 5x,'Lag',5x,' Q ',5x,' DF',5x,' P',/, 5x,'---',5x,'-------',5x,'---',5x,'-----')(5x,i3,5x,f7.3,5x,i3,5x,f6.3)()('n',a,'q: ',i3)lb(a,'q$',i2.2,': ',f7.3,5x,i3,5x,f6.3)Box-Piercebp('acflimit: ',f7.4)('nsig',a,': ',i3)acf('sig',a,'$',i2.2,': ',f7.4,5x,f7.4,3x,f7.4)pacfacfdgn.f?Squared ResidualsResidualsRegression ResidualsSeries (Transformed, Preadjustedacfhdr.f(' Sample Partial Autocorrelations of the ',a)(' Sample Autocorrelations of the ',a,' with the ',a, ' diagnostic.')Ljung-BoxBox-Pierce(' Sample Autocorrelations of the ',a)(' Differencing: none')(' Differencing: Seasonal Order=',i1)(' Differencing: Nonseasonal Order=',i1)(' Differencing: Nonseasonal Order=',i1, ', Seasonal Order=',i1) adjustmentsspanERROR: Prior adjustment factors expressed as percentages cannot have valuesERROR: Prior adjustment factors expressed as ratios cannot have values less than or equal to zero. Check the prior adjustment factors given in your spec file.Y@Easter[StatCanEaster[ 8Stock Trading Day[Trading Day (after )Weekday (change for before (before Weekday I I (starting Weekday II IIEaster[StockEaster[StatCanEaster[8PLength-of-MonthLength-of-QuarterLeap Year (after )8 (change for before (before I (starting IIaddotl.f(/,' ERROR: Column, 1<=begcol<=endcol<= nb', /,25x,3I8,'.')(/,' NOTE: Removing ',a, ' from the regression because it is not within',/, ' the span of the data.',/)(/,' NOTE: Removing ',a, ' from the regression because it occurs at the',/, ' last data point of the span of the data.',/)(/,' NOTE: Removing ',a, ' from the regression because it occurs at the',/, ' first data point of the span of the data.',/)(/,' ERROR: ',a, ' not an AO, LS, TC, TL, SO, QD, QI or ramp outlier.')?addsef.f(/,' Column error, 1<=begcol<=endcol<= nb',/,26x,3I8) janfebmaraprmayjunjulaugsepoctnovStock Trading Day[Trading Day (after )1-Coefficient Weekday8 (change for before (before Weekday I I (starting Weekday II II054User-defined SeasonalUser-defined HolidayUser-defined Holiday Group 2User-defined Holiday Group 3User-defined Holiday Group 4User-defined Holiday Group 5User-defined?LOMLOQLPY+temporarypermanent  constseasonalsincostdtdnolpyearlomloqlpyeartdstocklomstockeastersceasterlaborthanktd1coeftd1nolpyeartdstock1coefeasterstockConstant8[LaborThanksgiving aolsrpmvtcsotlqiqdaoslssIrregular Component Regression variable name "" not foundRegression variable name "No time series specified for AO outliersSee the above AO, LS, RP, SO, TL, TC, QI, or QD error.Not within seriesAOMVNo time series specified for level-shiftLSNo time series specified for ramp variableEnd of ramp not within seriesBegining of ramp not within seriesBegining and end of ramp reversedRpNo time series specified for TC outliersTCNo time series specified for seasonal outliersSONo time series specified for temporary LS variableEnd of temporary LS not within seriesBegining of temporary LS not within seriesBegining and end of temporary LS reversedTLNo time series specified for quadratic ramp (QI) variableEnd of quadratic ramp (QI) not within seriesBegining of quadratic ramp (QI) not within seriesBegining and end of quadratic ramp (QI) reversedQINo time series specified for quadratic ramp (QD) variableEnd of quadratic ramp (QD) not within seriesBegining of quadratic ramp (QD) not within seriesBegining and end of quadratic ramp (QD) reversedQDNo time series specified for AO sequence (AOS) variableSee the above AOS or LSS error.End of AO sequence (AOS) not within seriesBegining of AO sequence (AOS) not within seriesBegining and end of AO sequence (AOS) reversedNo time series specified for LS sequence (LSS) variableEnd of LS sequence (LSS) not within seriesBegining of LS sequence (LSS) not within seriesBegining and end of LS sequence (LSS) reversedNo seasonal period specified to determine seasonal effects.Seasonal effects with nonseasonal data.Already have a seasonal difference in the identify spec.Already have seasonal effects or seasonal difference.Already have change of regime seasonal effects.SeasonalthMust specify the sine-cosine term explicitly.Already have a seasonal difference in the identify specAlready have seasonal effects or seasonal differencecos(2pi*t/Trigonometric Seasonalsin(2pi*adpdrg.f(/,' ERROR: Cannot have a sin-cos variable pair with,', ' i=',i4,'.',/)No seasonal period specified in series spec. Need monthly or quarterly data for trading dayNo trading variables before 1776. Try including the century in the start dateCannot use flow trading day regressors for stock series.Already have trading day effects.Already have change of regime trading day effects.)1-Coefficient Trading DayWeekdayTrading Day+* Can't add a length of month, quarter, or leap year variable when using the td or td1coef option.Can't add a length of month variable when using the leap yearCan't add a length of quarter variable when using the leap year variable.Cannot use flow length of month regressor for stock series.Cannot use flow length of quarter regressor for stock series.Length-of-Month!Length-of-Quarter"Can't add a leap year variable when using the length of monthCan't add a leap year variable when using the length of quarterCannot use flow leap year regressor for stock series.Leap Year#Cannot use stock length of month regressor for flow series.Can't add a stock length of month variable when using the leap year variable.Need monthly data for stock trading day Stock Length-of-Month% the start date.Cannot use stock trading day regressors for flow series.Must specify the Stock TD sample day explicitlyStock TD sample day must be (1:31)Stock Trading Day[Already have stock trading day effects.Already have change of regime stock trading day effects.1-Coefficient .0/$ Need monthly or quarterly data for an Easter effectNo Easter effect before 1901. Try including the century in the start date.Cannot use Easter regressor for stock series.Cannot use stock Easter regressor for flow series.Cannot compute holiday effect after 2100Must specify the Easter window length explicitlyThe Easter window must be from 1 to 25.The Statistics Canada Easter window must be from 1 to 24.StockEaster[Easter[StatCanEaster[StockEaster EasterStatCanEasterNeed monthly data for a Labor Day effectNo Labor Day effect before 1901. Try including the century inCannot use Labor Day regressor for stock series.A Labor Day regressor is already included in the regARIMA model.Must specify the Labor Day window length explicitlyThe Labor Day window must be from 1 to 25.Labor[Need monthly data for a Thanksgiving-Christmas day effectThanksgiving-Christmas day effect not defined before 1939. Try including the century in the start date.Cannot use Thanksgiving-Christmas regressor for stock series.A Thanksgiving-Christmas regressor is already included in the regARIMA model.Must specify the Thanksgiving day window length explicitlyThe Thanksgiving day window must be from -8 to 17 (excluding 0)Thanksgiving[ @@@@S@S@S@S@S@@S@c@c@{@@S@S@@c@@@@@@@/@E@[@q@@@adrgef.f(/,' ERROR: ',a,' already exists.')(/,' ERROR: ',a,' is already in the regression.')P(/, ' ERROR: Adding ',a,' exceeds the number of regression ', 'effects allowed',/, ' in the model (',a,').',//, ' Check the regression model, change the ', 'automatic outlier options,',/, ' (e.g. method to ADDONE, raise the critical ', 'value, or change types',/ ' to identify AOs only), or change the program ', 'limits (see ',a,/, ' of the ',a,' ',a,').')Section 2.7X-13ARIMA-SEATSReference Manualmontuewedthufrisat janfebmaraprmayjunjulaugsepoctnovDate given for change of regime not within the series.Leap Year (after )Leap Year8 (change for before I (before (starting II (change for after P (after Leap Year (change for before Leap Year ILeap Year (before Leap Year (starting #Leap Year IILeap Year (change for after adsncs.f(/,' Column error, 1<=begcol<=endcol<= nb',/,26x,3I8)sinPERT!@ ?Pagr2.f(' NOTE: Comparison diagnsotics for composite adjustment', ' cannot be generated ',/, ' when SEATS cannot perform a signal extraction ', 'on the composite data.')(/,35X,'Full Series Last 3 Years')(a,3x,2F15.3) R1 (MSE percent change) : R1 (RMSE percent change) : R2 (MSE percent change) : R2 (RMSE percent change) : (a) 1(8X,28A4)(/,38X,'MEASURES OF ROUGHNESS R1 AND R2', ' FOR SEASONALLY ADJUSTED SERIES',/,37X,16A4//)(/,38X,'MEASURES OF ROUGHNESS R1', ' FOR SEASONALLY ADJUSTED SERIES',/,37X,16A4//)(48X,'DIRECT',22X,'INDIRECT',17X,'PERCENTAGE CHANGE')(48X,'------',22X,'--------',17X,'-----------------',/)(/,51X,' LAST THREE',17X,' LAST THREE',17X, ' LAST THREE'/,39X,' FULL SERIES',5X,'YEARS',7X, ' FULL SERIES',5X,'YEARS',7X,' FULL SERIES',5X,'YEARS', //,8X,' R1-MEAN SQUARE ERROR ',2(5X,2F12.3),5X, 2(F11.3,'%'),//,8X,' R1-ROOT MEAN SQUARE ERROR', 2(5X,2F12.3),5X,2(F11.3,'%'),//)(8X,' R2-MEAN SQUARE ERROR ',2(5X,2F12.3),5X, 2(F11.3,'%'),//,8X,' R2-ROOT MEAN SQUARE ERROR', 2(5X,2F12.3),5X,2(F11.3,'%'))(/8X,'POSITIVE PERCENTAGE CHANGES INDICATE THAT THE INDI', 'RECT SEASONALLY ADJUSTED',/,8X, 'COMPOSITE IS SMOOTHER THAN THE DI', 'RECT SEASONALLY ADJUSTED COMPOSITE.')r1mse: r1rmse:r2mse: r2rmse:(' NOTE: Aggregation cannot be done when SEATS ', 'cannot perform a signal',/, ' extraction on the data.')(' ERROR : Series ',a,' has non-overlapping time span.',/, ' Aggregation not computed.')Y@A ('1',///,a,a,//,a, 'Indirect Seasonal Adjustment of Composite Series',//,a, 'U. S. Census Bureau, Release Version ',A,' Build ',a,///)X-13ARIMA-SEATS1.126(6X,'Series Title- ',A80,/,6X,'Series No. ',A)(6x,a)(/,a,'Period Covered- ',I2,'/',I4,' to ',I2,'/',I4,'.')('0',//,a,'There are ',I5,' components in the composite.')(//,' Summary of component series:',//, ' Composite Composite',/, ' Type Weight Spec file for series',/, ' --------- --------- ', '-----------------------------------------------')(6x,a4,9x,f7.3,7x,a)('indirect: ',i5)('indtrendma: ',i3) QP$C % &'L( )M('indforce: ',a)yesnoFWG*N +,OSTRagr3.f?-C6?A ('1',///,a,a,//,a, 'Indirect Seasonal Adjustment of Composite Series',//,a, 'U. S. Census Bureau, Release Version ',a,' Build ',a,///)X-13ARIMA-SEATS1.126(6X,'Seires Title- ',A80,/,6X,'Series No. ',A)(6x,a)(/,a,'Period Covered- ',I2,'/',I4,' to ',I2,'/',I4,'.')('0',//,a,'There are ',I5,' components in the composite.')(//,' Summary of component series:',//, ' Composite Composite',/, ' Type Weight Spec file for series',/, ' --------- --------- ', '-----------------------------------------------')(6x,a4,9x,f7.3,7x,a)('indirect: ',i5)QP &'L )M('indforce: ',a)yesnoFWG01234567=>agr3s.fNOTE: Insufficient data to compute average forecast error diagnostic.xK T7B?Y@@8(//,' ARIMA Estimates and Likelihood Values for ARMA ', 'Order Identification',/)(/,' ERROR: Cannot make a choice of ',a,' ARMA order due', ' to', /,' model estimation errors within the automatic ', 'model',/,' selection procedure.')seasonalnonseasonal(' ichk (best model vrs. model ',i1,') = ',i3)(/,' ERROR: Estimation failed to converge for ', 'automatically identified model', /,' when convergence tolerence reset to ',e13.6)(/,' Rerun program trying one of the following:',/, 10x,'(1) Allow more iterations (set a larger value of ', 'maxiter).', /,10x,'(2) Try a different model or different modeling ', 'options.',/, /,1x,'See ',a,' of the ',a,' ',a,' for more discussion.')Section 5X-13ARIMA-SEATSReference Manual(//,' Best Five ARIMA Models',/)(' Model # ',i2,' : ',a,t40,'(BIC = ',f10.3,')')(/,' Automatic model choice : ',a)amdid.fMbP?8~jth??Q??{Gz?{Gzd?Q~?amdid2.f(/,' ERROR: Unable to set up ARIMA model for automatic ', 'model identification',/, ' procedure for the reason(s) given above.')(/,' NOTE: Estimation error found during automatic model ', 'selection procedure', /,' while estimating inital values for ARIMA model', ' coefficients.', /,' Try setting hrinitial=no.')amdprt.f(' Model Estimated : (',3(i2,1x),') (',3(i2,1x),')')(' Estimation errors cause model (',3(i2,1x), ') (',3(i2,1x),') to be skipped')(' -----')(' Model Estimated : (',3(i2,1x),')')(' Estimation errors cause model (',3(i2,1x), ') to be skipped')(a,4f10.4) Regular AR : Seasonal AR : Regular MA : Seasonal MA : BIC : BIC2 : (' Rerun program trying one of the following:',/, ' (1) Allow more iterations (set a larger ', 'value of maxiter).',/, ' (2) Lower one of the values of maxorder.', ' See ',a,' of the ',a,' ',a,' for more',/, ' discussion.')Section 5X-13ARIMA-SEATSReference Manual(/,3x,'No models have been selected due to errors in model', ' estimation.')noneERROR: A model estimation error has occurred during outlier identification within the automatic model identification procedure; for more details, check the error file ().amidot.fEHI(i4,"*",a)(i4,'*',2x,a,3x,a,6x,a,8x,a,3x,i2,3x,i2,3x,i2,3x,i2,4x,i2,4x, i2,4x,i2,2x,f9.0,2x,f9.0, 5x,a,7x,a,7x,a,2x,a,x,a,x,a, 5x,a,2x,a)uJ(i4,'*',2x,a,x,f9.0,x,f9.0,x,f9.0,x,f9.0,x,f9.0,4x,f9.0, x,f9.0,4x,f9.0,x,f9.0,x,f9.0,x,f9.0,x,f9.0,x, f9.0,x,f9.0)( i4,'*',2x,a,x,f9.0,x,f9.0,x,f9.0,x,f9.0,11x,i2, 8x,i2,8x,i2,4x,f9.0,x,f9.0 )--6572012/11/28 12:09:23Revision: Build: "(//,6X,'INCORRECT NUMBER OF OBSERVATIONS')(6X,'FOR THE SERIES : ',A,//)Incorrect number of observationsp,n,s,erp,n,erError reading SEATS parameters(//,6x,'ERROR IN THE NAMELIST "INPUT" ')(6x,'FOR THE SERIES : ',a,//)p,n,s,er,cyp,n,er,cyNY\moments\acfes.mP\moments\vares.mQ\moments\ccfes.mR\summarys.txt.sumAError opening summarys.txt(3x,A)(3x,'NZ =',I3.3,';',3x,'PERIOD=', I2.2,'-'I4.4,'/',I2.2,'-',I4.4,';', 3x,'MQ='I2.2,';',/)(3x,'INPUT ') .par(3x,'n',3x,'Title',17x,'NAiter Q-val', 2x,'PHI1',4x,'PHI2',4x,'PHI3',4x,'BPHI',5x, 'm (p d q)(bp bd bq)',3x, 'TH1',5x,'TH2',5x,'TH3',5x,'BTH',8x,'Mean')\sgeneral.m.gen(3x,'n',3x,'Title',17x,'Pread.',x, 'Model',3x, 'Approx.',15x,'Model',20x,'SD(a)',4x, 'SEAS_NP(a)',2x,'Spectr.',x,'Check',2x, 'Check',5x,'Determ.')(36x,'Changed',x,'to NA',63x,'Factor', 2x,'on ACF',x,'on CCF',2x,'Comp. Modif.')(53x,'m',4x,'p',4x,'d',4x, 'q',4x,'bp',4x,'bd',4x,'bq', 48x,'TC',x,'S',x,'U',x, 'Trans',x,'SA')sparami.mBsparamii.m_smi.par_smii.parC(3x,'n',3x,'Title',43x,'SD(innov)',36x, 'SE Est.',16x,'SE Rev.',21x, 'SE : Rates of Growth')(100x,'(Conc.)',16x,'(Conc.)', 16x,'SE T11',19x,'SE T1Mq')(142x,'(One Period)',11x, '(Annual Centered)')(33x,'TC',9x,'S',5x,'Trans',5x,'StocTD', 8x,'U',8x,'SA',11x,'TC',8x,'SA',11x,'TC',8x, 'SA',12x,'TC',8x,'SA',9x,'X',8x,'TC', 8x,'SA')(3x,'n',3x,'Title',36x,'Convergence', 23x,'Signif.Stoch.',21x,'DAA')(50x,'(in %)',26x,'Season. (95%)')(42x,'1Y',17x,'5Y')(37x,'TC',8x,'SA',8x,'TC',8x,'SA', 8x,'Hist.',5x,'Prel.',5x,'Fore.',11x,'TC', 8x,'SA').pksSA_ir.pksIrregular_tr.pksTrend-Cycle\ROGTABLE.OUT.rog6cTABLE-S.OUT.tbs$('M',i4.4,a)*TSeries No Treated in Tramo for Error$TSeries No Treated in Tramo#TModel especification error detected in Tramo(i4,a,x,a,3x,a,6x,a,8x,a,3x,i2,3x,i2,3x,i2,3x, i2,4x,i2,4x,i2,4x,i2,2x,f9.0,2x,f9.0,5x,a,7x,a,7x,a,2x,a, x,a,x,a,5x,a,2x,a)(i4,a,x,a,5(x,f9.0),2(4x,f9.0,x,f9.0),5(x,f9.0))(i4,a,x,a,x,f9.0,x,f9.0,x,f9.0,x,f9.0,11x,i2, 8x,i2,8x,i2,4x,f9.0,x,f9.0)(/,2x, 'FORECAST HORIZON > NZ. FH set to ',i2,'.',/)(2x, 'WARNING : The value entered for NZ is smaller ', 'than the number of observations in the series.')(12x, 'The program will use ',i3,' observations.')(//)(2x, 'WARNING : The value entered for NZ is greater ', 'than the number of observations in the series.')(12x, 'The program will use ',i3,' observations.')( ' PART 1 : ARIMA ESTIMATION',/,' -------------------------',// )(' METHOD: MAXIMUM LIKELIHOOD')(' METHOD: CONSTRAINED LEAST SQUARES')(/' NO OF OBSERVATIONS =',I3,//)(4x,"Due to FirstObs parameter:")(8x,"First(",i3.3,") observations in the ", "original series have been removed.",//)(4x,"Due to LastObs parameter:")(8x,"Last(",i3.3,") observations in the ", "original series have been removed.",//)(8x,"First(",i3.3,") observations in the ", "original series have been removed.",//)(8x,"Last(",i3.3,") observations in the ", "original series have been removed.",//)(2x,'MISSING OBSERVATIONS IN ORIGINAL SERIES',/,2x, 'HAVE BEEN INTERPOLATED',/)(//,' ORIGINAL UNCORRECTED SERIES (from regARIMA)')(/,' PREADJUSTMENT FACTORS',/, ' Outliers and Other Deterministic Effects',//, ' (from regARIMA)')(/,' PREADJUSTMENT COMPONENT',/, ' Outliers and Other Deterministic Effects',//, ' (from regARIMA)')(/,4x,A)Units in input series are too small.(4x,A,A,i2,A)It is recommended that the series be multiplied by 10**;(4x,A,/,4x,A)the program will do it automatically.(If correction is not desired, set UNITS=0)The output of the program refers to series multiplied by 10**.Units in input series are too large.(/,4x,A,A,i2,A) divided by 10**series divided by 10**(//,' ORIGINAL SERIES')(//, ' ARIMA SERIES',/,' (Corrected by regARIMA)',/ ' "Original Series" FOR SEATS')(/,4x,'DETERMINISTIC EFFECTS ASSIGNED ', 'TO THE SEASONAL COMPONENT',/,4x,'HAVE BEEN CENTERED.')(/,4x,'DETERMINISTIC EFFECTS ASSIGNED ', 'TO THE SEASONAL COMPONENT',/,4x,'HAVE NOT BEEN CENTERED.')(/,4x,'DETERMINISTIC EFFECTS ASSIGNED ', 'TO THE IRREGULAR COMPONENT',/,4x, 'HAVE NOT BEEN CENTERED.')(/,4x,'DETERMINISTIC EFFECTS ASSIGNED ', 'TO THE TRANSITORY COMPONENT',/,4x, 'HAVE NOT BEEN CENTERED.')(//,2X,'BIAS SET EQUAL TO 1')(/,2x,'INPUT PARAMETERS',/2x, '----------------')(/2x,'LAM=',i2,8x,'IMEAN=',i2,8x, 'RSA=',i2,8x,'MQ=',i2)(2x,'P=',i2,10x,'BP=',i2,11x,'Q=',i2,10x, 'BQ=',i2)(2x,'D=',i2,10x,'BD=',i2,11x, 'NOADMISS=',i2,3x,'RMOD=',f8.3)(2x,'M=',i2,10x,'QMAX=',i2,9x, 'BIAS=',i2)(2X,'THLIM=',F7.3,2X,'THLIM=',F7.3, 2x,'IQM=',i3,7x,'OUT=',i3)(2X,'EPSPHI=',F6.3,1X,'MAXIT=',i3,7x, 'XL=',f7.3,4x,'STOCHTD=',i2)*(//,8X,A,//)FREQUENCY OF OBSERVATIONS NOT APPROPIATE FOR SEATS(/' TRANSFORMATION: Z -> LOG Z')(/4X,'Ilam CHANGED TO 1 SERIES HAS NEGATIVE VALUES',/) ( /,' ONLY ALLOWS 48 AUTOCORRELATIONS-',i4, ' IS TOO MANY')s2Linealized Series Xl?V XWY(//,/,' CORRECTED MEAN OF DIFF. SERIES =', d12.4)LqExtended Residuals Atr(i4,x,A)(7x,A,6x,A,8x,A,4x,I1,4x,I1,4x,I1, 4x,I1,5x,I1,5x,I1,5x,I1,2x,g11.4,5x,g11.4,5x,A,7x,A, 7x,A,2x,A,x,A,x,A,5x,A,2x,A)stocTDTrans (3x,'Decomposition : Standard Errors')(26x,'SD(innov)',28x, 'SE Est.',16x,'SE Rev.')(63x,'(Conc.)',16x,'(Conc.)')(8x,'TC',9x,'S',5x,A6,8x, 'U',8x,'SA',11x,'TC',8x,'SA',11x,'TC',8x, 'SA')(5x,g11.4,1x,g11.4,1x,g11.4,1x,g11.4,1x, g11.4,4x,g11.4,x,g11.4,4x,g11.4,x,g11.4)(14x,'SE : Rates of Growth')( 9x,'SE T11',19x,'SE T1Mq')(6x,'(One Period)',11x, '(Annual Centered)')(8x,'TC',8x,'SA',9x,'X',8x,'TC', 8x,'SA')(x,f9.2,x,f9.2,x,f9.2,x,f9.2,x,f9.2)(5x,f9.1,1x, f9.1,1x,f9.1,1x,f9.1,11x,I2,8x,I2,8x,I2, 4x,f9.2,1x,f9.2)(x,"Model for the components:")(2x,"Trend-cycle:")(2x,A)(2x,"Seasonal:")(2x,"SA series:")(2x,"TD stoch.:")(2x,"Transitory:")(2x,"Irregular:")(i4,3x,a,3x,a,6x,a,8x,a,4x,i1,4x,i1,4x,i1, 3x,i1,5x,i1,5x,i1,5x,i1,4x,g11.4,5x,g11.4, 3x,a,7x,a,6x,a,3x,a,1x,a,1x,a,5x,a,2x,a)(i4,3x,a,6(x,g11.4),4x,g11.4,x,g11.4,4x, g11.4,x,g11.4,x,f9.2,x,f9.2,5x, g9.2,x,g9.2,x,g9.2)(i4,3x,a,1x,f9.1,1x, f9.1,1x,f9.1,1x,f9.1,11x,I2,8x,I2,8x,I2, 4x,f9.2,1x,f9.2)(//,4x,A,A,i2,A,//)WARNING : to recover the units of the original input file, the series should be multiplied by 10**(/,4x,A,A)WARNING : To recover the units of the original input filethe series should be multiplied by 10**the series should be divided by (//,2x,'RESETTING INIT = 0 BECAUSE RESIDUAL', ' LJUNG-BOX Q (',F12.3,') > QMAX (',I5,')')(/,2X,' BQ GREATER THAN ',I1)(/,2X,' BP GREATER THAN ',I1)(/,2X,' Q GREATER THAN ',I2)(/,2X,' P GREATER THAN ',I2)( /,' THE INITIAL VALUES OF THETA AND PHI ARE EQUAL ;', ' THE MODEL IS DEGENERATE')( /,' THE INITIAL VALUES OF BTHETA AND BPHI ARE EQUAL ;', ' THE MODEL IS DEGENERATE')(4X,'NOT ENOUGHT OBSERVATIONS')(4X,A)WARNING : POSSIBLE ERROR IN SERIES LENGTH(14X,A,/,14X,A)PLEASE CHECK SERIES LENGTHFOR THE SERIES :(14X,A)NOT ENOUGHT OBSERVATIONS(i4,'$',2x,a,3x,a,6x,a,8x,a,3x,i2,3x,i2,3x,i2,3x,i2,4x,i2,4x, i2,4x,i2,2x,f9.0,2x,f9.0,5x,a,7x,a,7x,a,2x,a,x,a,x, a,5x,a,2x,a)(i4,'$',2x,a,x,f9.0,x,f9.0,x,f9.0,x,f9.0, x,f9.0,4x,f9.0, x,f9.0,4x,f9.0,x,f9.0,x,f9.0,x,f9.0,x,f9.0,x, f9.0,x,f9.0)( i4,'$',2x,a,x,f9.0,x,f9.0,x,f9.0,x,f9.0,11x,i2, 8x,i2,8x,i2,4x,f9.0,x,f9.0 )( //,4x,' NO STOCHASTIC DECOMPOSITION IS PERFORMED FOR A ', 'NOISE OR PURELY ,MOVING AVERAGE MODEL', /,8x,' P+D+BP+BD>0 IS REQUIRED ')(//,4x, 'STOCHASTIC SA SERIES = LINEARIZED SERIES')! (i4,'^',2x,a,3x,a,6x,a,8x,a,4x,i1,4x,i1,4x,i1,4x,i1,5x,i1,5x, i1,5x, i1,4x,g11.4,5x,g11.4,3x,a,7x,a,6x,a,3x,a,x,a,x,a, 5x,a,2x,a)-(i4,'^',2x,a,x,g11.4,x,g11.4,x,g11.4,x,g11.4, x,g11.4,x,g11.4,4x,g11.4, x,g11.4,4x,g11.4,x,g11.4,x,g11.4,x,f9.2,9x,a,9x, a,9x,a)( i4,'^',2x,a,x,f9.1,x,f9.1,x,f9.1,x,f9.1,11x,i2, 8x,i2,8x,i2,4x,f9.2,x,f9.2 )B(7x,a,6x,a,8x,a,4x,i1,4x,i1,4x,i1,4x,i1,5x,i1,5x, i1,5x,i1,4x,g11.4,5x,g11.4,3x,a,7x,a,6x,a,3x,a,x,a,x,a, 5x,a,2x,a)(26x,'SD(innov)',28x, 'SE Est.',16x,'SE Rev.')(8x,'TC',9x,'S',5x,'Trans',9x, 'U',8x,'SA',11x,'TC',8x,'SA',11x,'TC',8x, 'SA')(5x,g11.4,x,g11.4,x,g11.4,x,g11.4,x, g11.4,4x,g11.4,x,g11.4,4x,g11.4,x,g11.4)(6x,'(One Period)',11x, '(Annual Centered)')(8x,'TC',8x,'SA',9x,'X',8x,'TC', 8x,'SA')(x,f9.2,x,f9.2,9x,a,9x,a,9x,a)(2x,f8.1,x,f9.1,x,f9.1,x,f9.1,11x,I2,8x,I2,8x,I2, 4x,f9.2,x,f9.2)(3x,'Model is a pure MA. ', 'Not decomposed by Seats.')SEATS RUN TIME ERROR(2X,'TYPE SHOULD BE EITHER 0 OR 1 ')(2x,'THE VARIABLE HAS TOO MANY OBSERVATIONS',/,2x, ' ONLY',i3,' ARE ALLOWED') WARNING : POSSIBLE ERROR IN INPUT FILE//Seats.log,analts.f@:0yE>@vIh%<=??@8@ffffff?ansub1.f( /,' ',' STARTING VALUES OUT OF RANGE', ' OR BOUNDS IN THE WRONG ORDER')( /,' '/' ITERATION ',i5,i12,' FUNCTION VALUES F = ', e17.8/(6e20.6))(/,'PARAMETER ',i2,' FIXED ')(/,' ',' MATRIX SINGULAR ')(/,' MODEL DEGENERATE - DET < 0')SEARCH : Model degenerate DET(A) <=0(/,' ',' GAMMA = ',f5.1)(/,' ',' INTERPOLATION ALONG OT ')(/,' ',' UNSUCCESSFUL ')(/,' ',' LAMBDA ADOPTED ',f12.3)(/,' ',' SPIRAL NUMBER ',i4)(/,' ',' INTERPOLATION ALONG SPIRAL STEP ',i4)(/,' ',' TAYLOR POINT ')(/,' ',' SUCCESSFUL ')(/,' ',' SUCCESSFUL AT STEP ',i4)(/,' ',' STEEPEST DESCENT ')( /,' ',' ALL PARAMETERS AT LIMITS ',10x,'F = ',e17.8/(6e20.6))(/,' MODEL DEGENERATE - DIAGONAL ELEMENT',i4,' SMALL')(/,' ELEMENT',i4,5x,f10.6)SEARCH : Model degenerate Diagonal Element too small(/,' ',' CORRELATION MATRIX ')(' ',(7f14.6))(/,' ',' STANDARD ERRORS OF PARAMETERS '/(1x,7f14.6))(/,' ',' EXACT FIT ')??-C6?& .>{Gz?Gz?KH9|=GܥL@??????vIh%<=(/,' AR AND MA HAVE COMMON FACTORS')(/,' DETB ZERO OR NEGATIVE')CALCFX : Error DET(B) Zero or Negative@z????@??(' PARAMETER SET AWAY FROM BOUNDARY,I=',i2)?& .>P??`ff??AUTO: Cannot generate autocorrelations from a series of zeros.???("!!!!Error en PartAuto aumentar maxAutoCorr")(//37x,' FORECAST OF TRANSFORMED SERIES')('1',37x,'FORECAST OF ACTUAL SERIES')(2x, 'MAXIMUM ALLOWED VALUE FOR L IS ',i2,/,2x,'L CHANGED TO ' ,i2,/)-(//' ',16x,'LOWER LIMIT',19x,'FORECAST',16x, 'UPPER LIMIT')(/,' ',3f27.6)(/,' CUBIC ITERATIONS EXCEEDED')?@?@"@;@;-C6 ?@???hU?@??????-q=@?333333?\(\?\(\?{Gz?Y@?(4X,'BD CHANGED TO ',I1)(4X,'BQ CHANGED TO ',I1)(4X,'THE MODEL IS CHANGED AND RE-ESTIMATED')(4X,'BP CHANGED TO ',I1)(4X,'P CHANGED TO ',I1)(4X,'D CHANGED TO ',I1)-q=:0yE>|=?& .>?{Gz??@?@"@;@;-C6 ?ij@{Gz?@?& .>Y(2x,"The negative seasonal correlation - ", "possibly induced by seasonal adjustment- ",/,2x, "is ignored. Model from regARIMA has been modified by ", "setting BTH=0.")(2x,"A pure seasonal MA(1) does not yield ", "a proper seasonal component.",/,"Model from regARIMA ", "has been modified by setting BPHI=0")(2x,"MODEL CHANGED TO :",/,2x,"(",1x,i1, ",",2x,i1,",",2x,i1, ",",1x,")",4x,"(",1x,i1,",",2x,i1,",",2x,i1,1x,")")?B<@???0@@LONG TERM TRENDSA series without BCSeries without BCansub10.f(/,2X,"STOCHASTIC CYCLICAL COMPONENT")(/,2X,"REGRESSION CYCLICAL COMPONENT")(/,2X,"TOTAL CYCLICAL COMPONENT") (/2X,'Revision error of CYCLICAL COMPONENT')(/,2x,'STOCHASTIC ',A)(/,2x,'REGRESSION ',A)(/,2X,'TOTAL ',A) (/2X,'Revision error of ',A)(/,2X,"CYCLICAL COMPONENT")(/,2X,A)(/,2X,"STOCHASTIC CYCLICAL FACTOR")(/,2X,"REGRESSION CYCLICAL FACTOR")(/,2X,"TOTAL CYCLICAL FACTOR")(/2X,'Revision error of CYCLICAL FACTOR')(/,2x,'TOTAL ',A)(/,2X,'STOCHASTIC ',A)(/,2X,'REGRESSION ',A)(/,2X,"CYCLICAL FACTORS")(/,2X,A," COMPONENT")Y@(4X, "X 10.0D",I2,/)(/,1x,'YEAR',2x,12(6x,a4)/)(/,3x,'YEAR',5x,6(6x,a4)/)(/,3x,'YEAR',5x,4(6x,a4)/)(1X,"FORECAST : ")|=?@$(///," PART 5 : RATES OF GROWTH",/, " ------------------------",//)(3x,"THE RATE-OF-GROWTH OF SERIES Z(t) OVER", " THE PERIOD (t1,t2) IS EXPRESSED",/,3x, "IN PERCENT POINTS AS",/,24x, "[ (Z(t2) / Z(t1)) -1] * 100",/)(/,3x,"ALL STANDARD ERRORS REPORTED FOR THE ", "RATES-OF GROWTH IN THE FOLLOWING TABLES ARE COMPUTED",/,3x, "USING LINEAR APPROXIMATION TO THE RATES.",/,3x, "WHEN PERIOD-TO-PERIOD CHANGES ARE LARGE, THESE STANDARD", " ERRORS SHOULD BE INTERPRETED",/,3x, "AS BROAD APPROXIMATIONS, THAT WILL TEND TO ", "UNDERESTIMATE THE TRUE VALUES",/)(/,3x,"THE ERROR VARIANCES ARE BASED ON THE ", "ESTIMATION ERROR OF THE STOCHASTIC TREND AND SA",/,3x, "SERIES, AND THE ERRORS IN THE PARAMETER ESTIMATES ", "ARE NOT CONSIDERED.",/,3x,"GIVEN THAT THE ", "VARIANCES OF THE LATER GO TO ZERO AS t BECOMES ", "LARGE, THEY WILL TYPICALLY",/,3x,"BE DOMINATED ", "BY THE ESTIMATION ERROR VARIANCE OF THE STOCHASTIC ", "COMPONENTS.",/,3x,"(THIS DOMINANCE WILL BE ", "WEAKEST IN THE VICINITY OF OUTLIERS.)",/)(3x,"GROWTH OF SERIES Z(t) OVER THE PERIOD", " (t1,t2) IS EXPRESSED AS",/,24x,"[ Z(t2) / Z(t1)]")(/,3x,"THE ERROR VARIANCES ARE BASED ON THE ", "ESTIMATION ERROR OF THE STOCHASTIC TREND AND SA",/,3x, "SERIES, AND THE ERRORS IN THE PARAMETER ESTIMATES ", "ARE NOT CONSIDERED.",/,3x,"GIVEN THAT THE ", "VARIANCES OF THE LATER GO TO ZERO AS t BECOMES ", "LARGE, THEY WILL TYPICALLY BE DOMINATED",/,3x, "BY THE ESTIMATION ERROR VARIANCE OF THE STOCHASTIC ", "COMPONENTS.",/,3x,"(THIS DOMINANCE WILL BE ", "WEAKEST IN THE VICINITY OF OUTLIERS.),/")(/,3x,'SINCE THE SERIES IS MODELLED IN LEVELS', ' AND ITS DECOMPOSITION IS ADDITIVE, THE',/,3x,a, '"RATES OF GROWTH" ARE SIMPLY DENOTED "GROWTH" OF ', 'THE SERIES IN QUESTION.',/,3x, 'This growth can be transformed easily into a rate ', '(dividing by the value at the',/,3x,'starting period ', 'and multiplying by 100).',/,3x, 'Alternatively, a usually good approximation can be ', 'obtained by re-running',/,3x, 'SEATS with LAM=0, the same model, and reestimating ', 'the parameters',/)(/,3x,'IN THE TABLES THAT FOLLOW :',//,3x,'ORIGINAL SERIES' ,/,3x,"---------------",/,18x, 'DENOTES THE OBSERVED SERIES, UNLESS ', 'THERE ARE MISSING VALUES,',/,18x, 'IN WHICH CASE IT DENOTES THE INTERPOLATED SERIES.'//,3x, 'TREND-CYCLE AND SA SERIES',/,3x,'-------------------------',/,29x,'DENOTE THE FINAL ESTIMATORS, WITH DETERMINISTIC ',/,29x, 'EFFECTS (IF PRESENT) INCLUDED.',/)(/,4x,"A. PERIOD-TO-PERIOD RATE-OF-GROWTH OF ", "THE SERIES. T(1,1)",/)(6x,'TABLE 5.1 RATE T(1,1) : ESTIMATION ERROR VARIANCE')(6x,'-------------------------------------------------')(8X,'(X 1.0D',I2,')',//)(/)(8x,"CONCURRENT ESTIMATOR",12x,"TREND-CYCLE",4x, "SA SERIES",/)(8X,"FINAL ESTIMATION ERROR",9X,F9.3,5X,F9.3,/)(8X,"REVISION ERROR",17X,F9.3,5X,F9.3,/)(8X,"TOTAL ESTIMATION ERROR"9X,F9.3,5X,F9.3,/)(15x,"(SD)",19x,"(",f9.3,")",3x, "(",f9.3,")",/)(//3x,"AS MENTIONED BEFORE, ", "FOR APPLIED PURPOSES, THE RELEVANT ERROR IS THE FULL ", "REVISION THE",/,3x,"MEASUREMENT WILL UNDERGO.",/,3x, "ACCORDINGLY, THE STANDARD ERRORS APPEARING IN MOST ", "OF THE NEXT TABLES ARE THE",/,3x,"ONES IMPLIED ", "BY THE REVISION ERROR.")(3x,"THESE S.E. CAN BE USED TO BUILD ", "CONFIDENCE INTERVALS AROUND THE CONCURRENT OR,",/,3x, "IN GENERAL, PRELIMINARY ESTIMATORS, THAT INDICATE ", "A LIKELY RANGE FOR THE EVENTUAL",/,3x,"FINAL ESTIMATOR.")(3x,"THE S.E. CAN ALSO BE USED TO TEST FOR ", "SPECIFIC HYPOTHESIS.",/,3x, "FOR EXAMPLE IN TABLE 5.2 (BELOW), LET RC(t) BE THE ", "CONCURRENT ESTIMATOR OF A RATE FOR ",/,3x,"PERIOD t. IF : " ,//,18x,"| RC(t)/SE[RC(t)] | > 1.645",//,3x "WE CAN REJECT (AT THE 90% LEVEL) THAT THE EVENTUAL ", "FINAL ESTIMATOR OF THE RATE",/,3x, "FOR PERIOD t COULD BE ZERO.")(//,6x,"TABLE 5.2 PERIOD-TO-PERIOD RATE T(1,1) ", "FOR THE MOST RECENT PERIODS")(6x,'---------------------------------------', '---------------------------')(19x,'With associated SE in Percent points.',//)(//,6x,"TABLE 5.2 PERIOD-TO-PERIOD GROWTH ", "T(1,1) FOR THE MOST RECENT PERIODS")(6x,"---------------------------------------", "---------------------------")(32X,"With associated SE.",//)(8x,'DATE',11x,'ORIGINAL',21x,'TREND-CYCLE', 24x,'SA SERIES',/,23x,'SERIES',/,46x,'ESTIMATE',12x, 'SER',11x,'ESTIMATE',12x,'SER',/)(5x,a3,"-",i4,5x,g11.3,14x,g11.3,3x,g11.3, 9x,g11.3,3x,g11.3)(5x,a3,"-",i4,5x,g11.3,14x,g11.3,3x,g11.3,9x, g11.3,3x,g11.3)(30x,'ORIGINAL SERIES',10x,'TREND-CYCLE',12x, 'SA SERIES')(4X,'T11 RATE :',20X,g10.3,12X,g10.3,12X,g10.3,/)(/,4x,'B. ACCUMULATED RATE OF GROWTH DURING ', 'THE PRESENT YEAR.',/)(/,6x,'TABLE 5.3 ACCUMULATED RATE OF GROWTH ', 'DURING THE PRESENT YEAR')(6x,'------------------------------------', '------------------------')(30X,'(In percent points)',//)(8x,a3,'-',i4,18x,'ESTIMATE',14x,'SER',/)(8x,'ORIGINAL SERIES',8x,g11.3,13x,'-',/)(8x,'TREND-CYCLE',12x,g11.3,5x,g11.3,/)(8x,'SA SERIES',14x,g11.3,5x,g11.3,/)(/,6x,'TABLE 5.3 ACCUMULATED GROWTH DURING THE PRESENT YEAR') (6x,'------------------------------------', '------------------------',//)(4x,'ACCUMULATED RATE :',12x,g10.3,12x,g10.3,12x, G10.3,/)(/,4X,'C. RATES OF ANNUAL GROWTH T(1,MQ)',/)(/,4X,'C. ANNUAL GROWTH T(1,MQ)',/)(/,6x,'TABLE 5.4 ESTIMATION ERROR VARIANCE :',/,6x, '-------------------------------------',/,8x, 'Rate of annual growth T(1,MQ), not-centered and',/,8x, 'dated at last observation.')(/,6x,'TABLE 5.4 ESTIMATION ERROR VARIANCE :',/,6x, '-------------------------------------',/,8x, 'Annual growth T(1,MQ), not-centered and dated ',/,8x, 'at last observation.')(8X,'(X 1.0D',I1,')',//)(//)(8x,'CONCURRENT ESTIMATOR',12x,'TREND-CYCLE', 8x,'SA SERIES',/)(8x,'FINAL ESTIMATION ERROR',12x,f9.3,8x,f9.3,/)(8x,'REVISION ERROR',20x,f9.3,8x,f9.3,/)(8x,'TOTAL ESTIMATION ERROR',12x,f9.3,8x,f9.3,/)(12x,'(SD x 1.0D',i1,')',15x,'(',f9.3,')', 7x,'(',f9.3,')',/)(/,6x,'TABLE 5.5 INTERANNUAL RATE OF GROWTH :', /,6x,'--------------------------------------',/,8x, 'Rate T(1,MQ), not-centered and dated at last observation,' ,/,8x,'FOR THE MOST RECENT PERIODS.',/,8x, 'This rate measures the rate of growth with respect', ' to 1-year ago.',/,8x,'With standard errors.',/,8x, 'In Percent points.',//)(/,6x,'TABLE 5.5 INTERANNUAL RATE OF GROWTH :', /,6x,'--------------------------------------',/,8x, 'Growth T(1,MQ), not-centered and dated at last observation,' ,/,8x,'FOR THE MOST RECENT PERIODS.',/,8x, 'This rate measures the growth with respect to 1-year ago.' ,/,8x,'With standard errors.',//)(8x,'DATE',9x,'ORIGINAL',21x,'TREND-CYCLE', 24x,'SA SERIES',/,21x,'SERIES',/,46x,'ESTIMATE',12x, 'SER',11x,'ESTIMATE',12x,'SER',/)(5x,a3,'-',i4,5x,g11.3,14x,g11.3,3x, g11.3,9x,g11.3,3x,g11.3)(4x,'INTERANNUAL RATE :',12x,g10.3,12x,g10.3, 12x,g10.3)(5X,'(non_centered)',/)(/,3x,'THE ANNUAL RATE OF GROWTH IN TABLE 5.5', ' MEASURES GROWTH WITH RESPECT TO ONE-YEAR AGO',/,3x, 'BECAUSE IT IS NOT CENTERED, THE MEASURE INDUCES ', 'AN IMPORTANT PHASE EFFECT,',/,3x, 'AND CAN BE STRONGLY INFLUENCED BY THE IRREGULAR ', 'AND MOVING SEASONAL COMPONENTS.',/,3x'IT IS THUS A ', 'POOR INDICATOR OF THE PRESENT RATE OF ANNUAL',/,3x, 'GROWTH, USEFUL IN SHORT-TERM ANALYSIS.')(/,3x,'ASSESSMENTS ON THE PRESENT RATE OF ', 'ANNUAL GROWTH SHOULD BE PREFERABLY BE BASED',/,3x, 'ON THE CENTERED MEASUREMENT OF TABLE 5.6 BELOW, ', 'WHICH REQUIRES HALF-A-YEAR',/,3x, 'OF FORECAST. THIS CENTERING MINIMIZES PHASE EFFECT ', 'AND IS LESS AFFECTED BY THE',/,3x, 'IRREGULAR OR SEASONAL INNOVATIONS.')(/,6x,'TABLE 5.6 PRESENT RATE OF ANNUAL GROWTH :',/,6x, '-----------------------------------------',/,8x, 'Rate T(1,MQ), centered and dated ', 'Annual rate computed as the rate of growth ',/,8x, 'over the last (MQ/2) observed periods and ', 'the next (MQ/2) forecasts',/,8x,'at last observed period.' ,/,8x,'With associated standard errors.',/,8x, 'In Percent points.',//)(/,6x,'TABLE 5.6 PRESENT ANNUAL GROWTH :',/,6x, '---------------------------------',/,8x, 'Growth T(1,MQ), centered and dated at last observed period.', /,8x,'Annual growth computed as the growth ', 'over the last (MQ/2)',/,8x,'observed periods and ', 'the next (MQ/2) forecasts',/,8x, 'With associated standard errors.',//)(32x,'DATE',14x,'CENTERED RATE OF',10x,'SER', 17x,'TSE')(50X,'ANNUAL GROWTH',/)(8x,'ORIGINAL SERIES',7x,a3,'-',i4,12x, g11.3,8x,g11.3,8x,g11.3,/)(30x,a3,'-',i4,11x,'(',g11.3,')'6x,'(', g11.3,')',6x,'(',g11.3,')',/)(8x,'TREND-CYCLE',11x,a3,'-',i4,12x,g11.3, 8x,g11.3,8x,g11.3,/)(30x,a3,'-',i4,11x,'(',g11.3,')',6x,'(', g11.3,')',6x,'(',g11.3,')',/)(8x,'SA SERIES',13x,a3,'-',i4,12x,g11.3,8x, g11.3,8x,g11.3,/)(30x,a3,'-',i4,11x,'(',g11.3,')'6x,'(', g11.3,')',6x,'(',g11.3,')',/)(8x,'ORIGINAL SERIES',7x,a3,'-',i4,12x, g11.3,8x,g11.3,8x,g11.3,/)(8x,'TREND-CYCLE',11x,a3,'-',i4,12x,g11.3, 8x,g11.3,8x,g11.3,/)(30x,a3,'-',i4,11x,'(',g11.3,')',6x,'(', g11.3,')',6x,'(',g11.3,')',/)(8x,'SA SERIES',13x,a3,'-',i4,12x,g11.3,8x, g11.3,8x,g11.3,/)(8x,'ORIGINAL SERIES',7x,a3,'-',i4,12x,g11.3, 8x,g11.3,8x,g11.3,/)(8x,'SA SERIES',13x,a3,'-',i4,12x,g11.3,8x, g11.3,8x,g11.3,/)(30x,a3,'-',i4,11x,'(',g11.3,')',6x,'(', g11.3,')',6x,'(',g11.3,')',/)(8x,'ORIGINAL SERIES',7x,a3,'-',i4,12x,g11.3, 8x,g11.3,8x,g11.3,/)(30x,a3,'-',i4,11x,'(',g11.3,')'6x,'(', g11.3,')',6x,'(',g11.3,')',/)(8x,'TREND-CYCLE',11x,a3,'-',i4,12x,g11.3, 8x,g11.3,8x,g11.3,/)(8x,'SA SERIES',13x,a3,'-',i4,12x,g11.3,8x, g11.3,8x,g11.3,/)(4x,'PRESENT ANNUAL RATE :',9x,g10.3,12x,g10.3, 12x,g10.3)(8X,'(centered)',/)(/,4X,'D. FORECAST',/)(/,6x,"TABLE 5.7 RATES OF GROWTH FORECASTS :",/,6x, "-------------------------------------",/,16x, "In Percent Points",//)(4x,"FORECAST",22x,"ORIGINAL",16x, "TREND-CYCLE", 16x,"SA SERIES")(4X,"ORIGIN :",22X,"SERIES")(4x,a3,'-',i4,24x,'(SER)',22x,'(SER)', 22x,'(SER)',//)(2x,"ONE-PERIOD-AHEAD",/,2x,"FORECAST PERIOD ",/, 2x,"TO PERIOD RATE",13x,g11.2,16x,g11.2,15x,g11.2,/,2x, "T(1,1)",20x,"(",g11.2,")",14x,"(",g11.2,")",13x,"(",g11.2, ")"//)(2x,"FORECAST OF ANNUAL",/,2x, "RATE OF GROWTH OVER",/,2x,"THE NEXT ",i2," PERIODS", 8x,g11.2,16x,g11.2,15x,g11.2,/,2x, "(one year horizon)",8x,"(",g11.2,")",14x,"(",g11.2,")", 13x,"(",g11.2,")",//)(2x,"FORECAST OF ANNUAL",/,2x, "RATE OF GROWTH FOR",/,2x, "THE PRESENT YEAR",11x,g11.2,16x,g11.2,15x,g11.2,/,2x, "(December over December)",2x,"(",g11.2,")",14x, "(",g11.2,")",13x,"(",g11.2,")",//)(2x,"ONE-PERIOD-AHEAD",/,2x, "FORECAST PERIOD ",/,2x, "TO PERIOD RATE",13x,g11.2,16x,g11.2,15x,g11.2,/, 2x,"T(1,1)",20x, "(",g11.2,")",14x,"(",g11.2,")",13x,"(",g11.2, ")"//)(4x,"FORECAST OF T11 RATE :",8x,g10.3,11x,g10.3,12x,g10.3,/)(4x,"FORECAST 1-year ahead :",7x,g10.3,12x,g10.3,12x,g10.3,/)(4x,"FORECAST for present year :",3x,g10.3,12x,g10.3,12x, g10.3,///)Y@?|=@?Y@( //,2x,a,'STANDARD ERROR OF REVISION IN TREND-CYCLE ','ESTIMATOR' ,/,2x,'LAST 5 YEARS')FINITE SAMPLE ( //,2x,a,'STANDARD ERROR OF REVISION IN TREND-CYCLE ','ESTIMATOR' ,/,2x,'LAST YEARS')( //,2x,a,'STANDARD ERROR OF REVISION IN SA SERIES ','ESTIMATOR' ,/,2x,'LAST 5 YEARS')( //,2x,a,'STANDARD ERROR OF REVISION IN SA SERIES ','ESTIMATOR' ,/,2x,'LAST YEARS') (3x,'bd='I2)(A)(3x,'bias='I2)(3x,'acfe='I2)(3x,'printphtrf='I2)(3x,'Firstobs=',A)(3x,'Lastobs=',A)(3x,'bp='I2)(3x,'bq='I2)(3x,'centrregs='I2)(3x,'d='I2)(3x,'fh='I2)(3x,'fortr='I2)(3x,'har='I2)(3x,'hpcycle='I2)(3x,'imean='I2)(3x,'init='I2)(3x,'interp='I2)(3x,'iqm='I2)(3x,'iter='I2)(3x,'lam='I2)(3x,'m='I2)(3x,'maxit='I2)(3x,'model='I2)(3x,'mq='I2)(3x,'nochmodel='I2)(3x,'neast='I2)(3x,'noadmiss='I2)(3x,'noserie='I2)(3x,'nouir='I2)(3x,'nous='I2)(3x,'noutr='I2)(3x,'npareg='I2)(3x,'npatd='I2)(3x,'out='I2)(3x,'tabtables='3A)'(3x,'p='I2)(3x,'pg='I2)(3x,'q='I2)(3x,'qmax='I2)(3x,'rogtable='I2)(3x,'rsa='I2)(3x,'statseas='I2)(3x,'units='I2)(3x,'kunits='I2)(3x,'seas='I2)(3x,'sqg='I2)(3x,'tramo='I2)(3x,'type='I2)(3x,'blqt='f8.3)(3x,'crmean='I2)(3x,'epsiv='f8.3)(3x,'epsphi='f8.3)(3x,'hplan='f8.3)(3x,'hpPer='f8.3)(3x,'rmod='f8.3)(3x,'ta='f8.3)(3x,'thlim='f8.3)(3x,'bthlim='f8.3)(3x,'tmu='f8.3)(3x,'xl='f8.3)(3x,'phi(',I1,')=',f8.3)(3x,'th(',I1,')=',f8.3)(3x,'bphi(',I1,')=',f8.3)(3x,'bth(',I1,')=',f8.3)(3x,'PSIEINIC=',I4)(3x,'PSIEFIN=',I3)(3x,'MaxSpect=',F10.6)(3x,'Brol=',F10.6)(3x,'Blamda=',F10.6)(3x,'Bserie=',i2)(3x,'Bmid=',i2)(3x,'BcMark=',i2)(3x,'stochTD=',I3)(/,2x,'Wrong value for the parameter "ACFE"', /,2x,'Admissible value : [0..999]',/ 2x,'ACFE set to the default value.')(/,2x,'Wrong value for the parameter "POSBPHI"', /,2x,'Admissible value : [0,1]',/ 2x,'POSBPHI set to the default value.')(/,2x,'Wrong value for the parameter "Firstobs"', /,2x,'Admissible value : ['A,', ',A,']',/ 2x,'Firstobs set to the default value.')(/,2x,'Wrong value for the parameter "Lastobs"', /,2x,'Admissible value : ['A,', ',A,']',/ 2x,'Lastobs set to the default value.')(/,2x,'Wrong value for the parameters "Firstobs"', '",Lastobs"',/,2x,'Firstobs should be < Lastobs',/ 2x,'Firstobs,Lastobs set to the default value.')(/,2x,'Wrong value for the parameter "BD"',/, 2x,'Admissible value : [0, 1]',/ 2x,'BD set to the default value.')(/,2x,'Wrong value for the parameter "BIAS"',/, 2x,'Admissible value : [-1, 0, 1]',/ 2x,'BIAS set to the default value.')(/,2x,'Wrong value for the parameter "BP"',/, 2x,'Admissible value : [0, 1]',/ 2x,'BP set to the default value.')(/,2x,'Wrong value for the parameter "BQ"',/, 2x,'Admissible value : [0, 1]',/ 2x,'BQ set to the default value.')(/,2x,'Wrong value for the parameter "CENTRREGS"', /,2x,'Admissible value : [0, 1]',/ 2x,'CENTRREGS set to the default value.')(/,2x,'Wrong value for the parameter "D"',/, 2x,'Admissible value : 0<= d <=3',/ 2x,'D set to the default value.')(/,2x,'Wrong value for the parameter "FH"',/, 2x,'Admissible value : fh > 0',/ 2x,'FH set to the default value.')(/,2x,'Wrong value for the parameter "FORTR"',/, 2x,'Admissible value : [0, 1]',/ 2x,'FORTR set to the default value.')(/,2x,'Wrong value for the parameter "HAR"',/, 2x,'Admissible value : [0, 1]',/ 2x,'HAR set to the default value.')(/,2x,'Wrong value for the parameter "HPCYCLE"',/, 2x,'Admissible value : [-1, 0, 1, 2]',/ 2x,'HPCYCLE set to the default value.')(/,2x,'Wrong value for the parameter "HPLAN"',/, 2x,'Admissible value >0.0625',/ 2x,'HPLAN set to the default value.')(/,2x,'Wrong value for the parameter "HPPer"',/, 2x,'Admissible value >2.0 .',/, 2x,'HPper set to the default value.')(/,2x,'Wrong value for the parameter "IMEAN"',/, 2x,'Admissible value : [0, 1]',/ 2x,'IMEAN set to the default value.')(/,2x,'Wrong value for the parameter "INIT"',/, 2x,'Admissible value : [0, 1, 2]',/ 2x,'INIT set to the default value.')(/,2x,'Wrong value for the parameter "INTERP"',/, 2x,'Admissible value : [0, 1, 2]',/ 2x,'INTERP set to the default value.')(/,2x,'Wrong value for the parameter "IQM"',/, 2x,'Admissible value : iqm >= 0',/ 2x,'IQM set to the default value.')(/,2x,'Wrong value for the parameter "ITER"',/, 2x,'Admissible value : [0, 1, 2, 3]',/ 2x,'ITER set to the default value.')(/,2x,'Wrong value for the parameter "LAM"',/, 2x,'Admissible value : [0, 1]',/ 2x,'LAM set to the default value.')(/,2x, 'Wrong value for the parameter "NOCHMODEL"',/, 2x,'Admissible value : [0, 1]',/ 2x,'NOCHMODEL set to the default value.')(/,2x,'Wrong value for the parameter "M"',/, 2x,'Admissible value : m >= 0',/ 2x,'M set to the default value.')(/,2x,'Wrong value for the parameter "MAXIT"',/, 2x,'Admissible value : maxit > 0',/ 2x,'MAXIT set to the default value.')(/,2x,'Wrong value for the parameter "MODEL"',/, 2x,'Admissible value : [0, 1]',/ 2x,'MODEL set to the default value.')(/,2x,'Wrong value for the parameter "MQ"',/, 2x,'Admissible value : [1, 2, 4, 6, 12]',/ 2x,'MQ set to the default value.')(/,2x,'Wrong value for the parameter "NEAST"',/, 2x,'Admissible value : [0, 1]',/ 2x,'NEAST set to the default value.')(/,2x,'Wrong value for the parameter "NOADMISS"', /,2x,'Admissible value : [0, 1]',/ 2x,'NOADMISS set to the default value.')(/,2x,'Wrong value for the parameter "OUTNA"', /,2x,'Admissible value : [0, 1]',/ 2x,'OUTNA set to the default value.')(/,2x,'Wrong value for the parameter "STOCHTD"', /,2x,'Admissible value : [-1, 0, 1]',/ 2x,'StochTD set to the default value.')(/,2x,'Wrong value for the parameter "NOSERIE"',/, 2x,'Admissible value : [0, 1]',/ 2x,'NOSERIE set to the default value.')(/,2x,'Wrong value for the parameter "NOUIR"',/, 2x,'Admissible value : [0, 1]',/ 2x,'NOUIR set to the default value.')(/,2x,'Wrong value for the parameter "NOUS"',/, 2x,'Admissible value : [0, 1]',/ 2x,'NOUS set to the default value.')(/,2x,'Wrong value for the parameter "NOUTR"',/, 2x,'Admissible value : [0, 1]',/ 2x,'NOUTR set to the default value.')(/,2x,'Wrong value for the parameter "NPAREG"',/, 2x,'Admissible value : [0, 1]',/ 2x,'NPAREG set to the default value.')(/,2x,'Wrong value for the parameter "NPATD"',/, 2x,'Admissible value : [0, 1]',/ 2x,'NPATD set to the default value.')(/,2x,'Wrong value for the parameter "OUT"',/, 2x,'Admissible value : [0, 1, 2, 3]',/ 2x,'OUT set to the default value.')(/,2x, 'Wrong value for the parameter "TABTABLES"',/, 2x,'TABTABLES set to the default value.')(/,2x,'Wrong value for the parameter "P"',/, 2x,'Admissible value : 0<= p <=3',/ 2x,'P set to the default value.')(/,2x,'Wrong value for the parameter "PG"',/, 2x,'Admissible value : [0, 1]',/ 2x,'PG set to the default value.')(/,2x,'Wrong value for the parameter "Q"',/, 2x,'Admissible value : 0<= q <=3',/ 2x,'Q set to the default value')(/,2x,'Wrong value for the parameter "QMAX"',/, 2x,'Admissible value : qmax >= 0',/ 2x,'QMAX set to the default value.')(/,2x,'Wrong value for the parameter "ROGTABLE"', /,2x,'Admissible value : [0, 1]',/ 2x,'ROGTABLE set to the default value.')(/,2x,'Wrong value for the parameter "RSA"',/, 2x,'Admissible value : [0, 1, 2]',/ 2x,'RSA set to the default value.')(/,2x,'Wrong value for the parameter "STATSEAS"', /,2x,'Admissible value : [-1,0, 1]',/ 2x,'STATSEAS set to the default value.')(/,2x,'Wrong value for the parameter "UNITS"',/, 2x,'Admissible value : [-1, 0, 1]',/ 2x,'UNITS set to the default value.')(/,2x,'Wrong value for the parameter "SEAS"',/, 2x,'Admissible value : [0, 1]',/ 2x,'SEAS set to the default value.')(/,2x,'Wrong value for the parameter "SQG"',/, 2x,'Admissible value : [0, 1]',/ 2x,'SQG set to the default value.')(/,2x,'Wrong value for the parameter "TRAMO"',/, 2x,'Admissible value : [-1, 0, 1]',/ 2x,'TRAMO set to the default value.')(/,2x,'Wrong value for the parameter "TYPE"',/, 2x,'Admissible value : [0, 1]',/ 2x,'TYPE set to the default value.')(/,2x,'Wrong value for the parameter "CRMEAN"',/, 2x,'Admissible value : [0, 1]',/ 2x,'CRMEAN set to the default value.')(/,2x,'Wrong value for the parameter "EPSIV"',/, 2x,'Admissible value : epsiv > 0',/ 2x,'EPSIV set to the default value.')(/,2x,'Wrong value for the parameter "EPSPHI"',/, 2x,'Admissible value : epsphi >= 0.0',/ 2x,'EPSPHI set to the default value.')(/,2x,'Wrong value for the parameter "RMOD"',/, 2x,'Admissible value : 0.0 <= rmod <= 1.0',/ 2x,'RMOD set to the default value.')(/,2x,'Wrong value for the parameter "THLIM"',/, 2x,'Admissible value : -1.0 < thlim < 0.0',/ 2x,'THLIM set to the default value.')(/,2x,'Wrong value for the parameter "BTHLIM"',/, 2x,'Admissible value : -1.0 < bthlim < 0.0',/ 2x,'BTHLIM set to the default value.')(/,2x,'Wrong value for the parameter "XL"',/, 2x,'Admissible value : 0.0 < xl <= 1.0',/ 2x,'XL set to the default value.')(/,2x, 'Wrong value for the parameter "Psieinic"',/, 2x,'Admissible value : [-300..-24]',/ 2x,'Psieinic set to the default value.')(/,2x,'Wrong value for the parameter "Psiefin"',/, 2x,'Admissible value : [-1..36]',/ 2x,'Psiefin set to the default value.')(/,2x,'Wrong value for the parameter "Brol"',/, 2x,'Admissible value : [0:1.0]',/ 2x,'Brol set to the default value.')(/,2x,'Wrong value for the parameter "Blamda"',/, 2x,'Admissible value : [-3.0:3.0]',/ 2x,'Blamda set to the default value.')(/,2x,'Wrong value for the parameter "Bserie"',/, 2x,'Admissible value : [0,1,2,3]',/ 2x,'Bserie set to the default value.')(/,2x,'Wrong value for the parameter "BMid"',/, 2x,'Admissible value : [0,1]',/ 2x,'BMid set to the default value.')(/,2x,'Wrong value for the parameter "BcMark"',/, 2x,'Admissible value : [0,1]',/ 2x,'BcMark set to the default value.')?@DT!@?@@(6x,'Name of the series set: ',a)(6x,'Total number of the series in the set :', i5.5)(6x,'Number of series not treated because not ', 'enough observations, too many',/,6x,'zeros, too many ', 'constant values at the end, or too many missing',/, 6x,'observations :',i5.5)(12x,a)(6x,'Number of series that produced ', 'a Run-Time EXCEPTION :',i5.5)(6x,'Number of series that produced ', 'a Run-Time EXCEPTION in TRAMO :',i5.5)(6x,'Number of series not treated because not ', 'enough observations, too many',/,6x,'zeros, too many ', 'constant values at the end, or too many missing',/, 6x,'observations in TRAMO :',i5.5)i Fallxopnscalucpacyltperrg0rgsastpstnucrtprtsa(i2)(i4)00-0000(i2.2,"-",i4.4)(i12)RQ?,X@|=@|=@ؗҜ?f@( 7x,' REAL PART ',' IMAGINARY PART',' MODULUS ', ' ARGUMENT ',' PERIOD')(6x,f11.4,4x,f11.4,5x,f11.4,4x,f11.4,5x,a4)(6x,f11.4,4x,f11.4,5x,f11.4,4x,f11.4,1x,f11.4)?@-q=vIh%<=@"@;@r(?+Tv<@LXz~ @LXz?+Tv<@vIh%<=vIh%<=-q=9@?9$$@-C6?-q=9@?9$$@-C6?v@j@DT!@v@B<@(//,5x,A,/,4x, ' ---------------------------------------------------------')( 3x,' REAL PART ',' IMAGINARY PART',' MODULUS ', ' ARGUMENT',' PERIOD')(2x,f11.3,4x,f11.3,5x,f11.3,4x,f11.3,5x,a4)(2x,f11.3,4x,f11.3,5x,f11.3,4x,f11.3,1x,f11.3)( /,' ','THE LENGTH OF THE MA DOESN''T MATCH WITH THE ACF')(/,5x,'TOTAL SQUARED ERROR=',d15.7):0yE>??@f@-q=vIh%<=?vIh%<=f@H.! @v@?vIh%<=@:0yE>@-DT! @@@?vIh%<=(4X, 'X 10.0D',I2,/)(/,1x,'YEAR',2x,12(6x,a4)/)(/,3x,'YEAR',5x,6(6x,a4)/)(/,3x,'YEAR',5x,4(6x,a4)/)|=?@( ' ** ABNORMAL EXIT from RPQ ',a,': IFAIL',' =' ,i6)RPQ ** RPQ hard failure - execution terminated ** RPQ soft failure - control returned(a)=<B &y3:0yEV瞯<>$@`P:#B ;|=1111ansub4.f(//,4x,'WIENER-KOLMOGOROV FILTERS (ONE SIDE)',/, 4x,'------------------------------------')(/,4X,'TREND-CYCLE COMPONENT',/)(12(2X,F7.4))(/,4X,'SA SERIES COMPONENT',/)(/,4X,'SEASONAL COMPONENT',/)(/,4X,'TD STOCH. COMPONENT',/)(/,4X,'TRANSITORY COMPONENT',/)(/,4X,'IRREGULAR COMPONENT',/)(////,4x,'CONTRIBUTION OF ORIGINAL SERIES AND ', 'OF ITS INNOVATIONS TO THE ESTIMATOR',/,4x, 'OF THE COMPONENTS FOR THE PRESENT PERIOD.',/)(4x,'COMPONENT',22x,'TREND-CYCLE',18x, 'SEASONAL COMPONENT',14x,'TRANS.+IRREGULAR',/)(4x, 'CONTRIBUTION OF',3(8x,'OBSERVATION',4x,'INNOVATION'),/)(4X,'LAST PERIOD',2X,3(9X,F9.3,6X,F9.3),/)(4X,'NEXT PERIOD',2X,3(9X,F9.3,6X,F9.3),/)(4X,'1 YEAR AHEAD',1X,3(9X,F9.3,6X,F9.3),/)(4X,'2 YEAR AHEAD',1X,3(9X,F9.3,6X,F9.3),/)(/)(4x,'Check :',/,12x,'- The sum of the 3 ', 'weights associated with the observation,',/,14x, 'for the last period, should be 1.0.',/,12x, '- The same should happen with the 3 weights associated ', 'with the innovations for the last period.',/,12x, '- The sum of the 3 weights associated with the ', 'innovation, for future period,',/,14x, 'should be zero.',/)(4x,'Note : some examples',/,12x, '* If the last observation on the series has a ', 'relatively large weight for the seasonal',/,14x, 'component, the series contains a relatively ', 'important seasonal component.',/,12x, '* If next period innovation has a relatively ', 'large weight for the trend-cycle',/,14x, 'component, the estimator of this component ', 'will be strongly affected by the',/,14x, 'next period forecast error (i.e., the first ', 'revision of the concurrent',/,14x, 'estimator will be large).',/,12x, '* If the weight for some component, associated ', 'with the innovation two-year into',/,14x, 'the future is large, this would indicate that ', 'the estimator, after two years of',/,14x, 'revisions is still far from convergence.')(//)(4x,'DISTRIBUTION OF COMPONENT, ', 'THEORETICAL ESTIMATOR AND EMPIRICAL ESTIMATE',/,4x, '---------------------------', '--------------------------------------------',/)( /,' ',10x,'AUTOCORRELATION FUNCTION OF COMPONENTS', ' (STATIONARY TRANSFORMATION)'///)(///31x,'TREND-CYCLE'// ' LAG',10x,'COMPONENT',4x,'ESTIMATOR',4x,' ESTIMATE',6x,'SE'/)(i4,4x,3(2x,f11.3),8x,'(***)')(i4,4x,4(2x,f11.3))(///' VAR.(*)',3(2x,f11.3),8x,'(***)')(///' VAR.(*)',4(2x,f11.3))(///28x,'SA SERIES'// ' LAG',10x,'COMPONENT',4x,'ESTIMATOR',4x,' ESTIMATE',6x,'SE'/)(///33x,'SEASONAL'// ' LAG',10x,'COMPONENT',4x,'ESTIMATOR',4x,' ESTIMATE',6x,'SE'/)(///32x,'TD STOCH.'// ' LAG',10x,'COMPONENT',4x,'ESTIMATOR',4x,' ESTIMATE',6x,'SE'/)(///32x,'TRANSITORY'// ' LAG',10x,'COMPONENT',4x,'ESTIMATOR',4x,' ESTIMATE',6x,'SE'/)Evwxyz{|TU}~(///33x,'IRREGULAR'// ' LAG',10x,'COMPONENT',4x,'ESTIMATOR',4x,' ESTIMATE',6x,'SE'/)(2x,'(***) : Unreliable SE estimate.')(//,2x,'(*) IN UNITS OF VAR(A)')|=p= ף@x(///,2x,' FORECAST OF STOCHASTIC SERIES AND ', 'COMPONENTS (LEVELS)',/,2x, ' -----------------------------------------------------')(/, 1x,'PERIOD',10x,'SERIES',24x,' TREND-CYCLE',20x,'ADJUSTED',// 12x,'FORECAST',8x,'S.E.',9x,'FORECAST',10x,'S.E.',9x, 'FORECAST',9x,'S.E.'/)( 2x,i4,5x,G11.4,2x,G11.4,5x,G11.4,4x,G11.4,5x,G11.4,3x,G11.4)( //,' ',/1x,'PERIOD',13x,' SEASONAL FACTORS',//,18x,'FORECAST' ,10x,'S.E.',/)(2x,i4,11x,g11.4,4x,g11.4)(/8X,'THE APPROXIMATION WILL LIKELY INDUCE')(8X,'NOZERO IRREGULAR FORECASTS,')(8X,'AND HENCE THE FORECAST OF THE ADJUSTED')(8x,'SERIES WILL NOT BE THAT OF ', 'THE TREND-CYCLE')( //,' ',/1x,'PERIOD',20x,' SEASONAL FACTORS',17x,A, '. COMPONENT',//,16x,'FORECAST',10x,'S.E.',11x,'FORECAST' ,14x,'S.E.'/)(2x,i4,7x,g11.4,4x,g11.4,7x,g11.4,7x,g11.4)(/,30x,'DUE TO THE APPROXIMATION, THE S.E.',/, 30x,'OF THE COMPONENT MAY BE UNRELIABLE',/)Y@|=Y@@?@@(//,4x,'DETERMINISTIC COMPONENT (from regARIMA)', /,4x,'------------------------------------')(//,2X,'LEVEL SHIFT',/)(//,2X,'TRANSITORY OUTLIERS',/)(//,2X,'SEASONAL OUTLIERS',/)(//,2X,'EASTER EFFECT',/)(//,2X,'DETERMINISTIC TRADING DAY EFFECT',/)(/,2x,A)DETERMINISTIC SEASONAL COMPONENT(//,2x,'CALENDAR REGRESSION EFFECT',/)(//,2x,'TREND-CYCLE REGRESSION EFFECT',/)#(//,2x,'BUSINESS CYCLE REGRESSION EFFECT',/)(//,2x,'IRREGULAR REGRESSION EFFECT',/)(//,2x,'TRANS. COMPONENT REGRESSION ', 'EFFECT',/)(//,2x,'OTHER REGRESSION EFFECT IN SA SERIES',/)(//,2x,'FINAL DECOMPOSITION',/,2x, '-------------------') !(//2x,'SEPARATE REGRESSION EFFECT',/)(//,2x,'FINAL COMPONENT',/,2x, '---------------')(//,2X,'FINAL SEASONALLY ADJUSTED SERIES',/)(//,2X, 'FINAL SA SERIES WITH REVISED YEARLY',/)"Y(//,2X,'FINAL TREND-CYCLE',/)(//,2X,'FINAL SEASONAL',/)FINAL TD COMPONENT$FINAL TRANSITORY COMPONENT(//,2X,'FINAL TRANSITORY-IRREGULAR',/)(//,2X,'FINAL IRREGULAR COMPONENT',/)(4x,'The same as the stochastic irregular.')(//,1X,'FORECAST OF FINAL COMPONENT')(//4x,'THE FORECAST OF THE IRREGULAR ', 'ABSORBS')(4X,'THE EFFECT OF THE APPROXIMATION.')(//,2X,'LEVEL SHIFT (X100)',/)(//,2X,'TRANSITORY OUTLIERS (X100)',/)(//,2X,'EASTER EFFECT (X100)',/)(//,2X,'TRADING DAY EFFECT (X100)',/)DETERMINISTIC SEASONAL FACTORS(//,2x,'SEASONAL REGRESSION EFFECT FACTORS (X100)',/)(//,2x,'TREND-CYCLE REGRESSION EFFECT FACTORS (X100)',/)(//,2x,'BUSINESS CYCLE REGRESSION EFFECT FACTORS (X100)',/)(//,2x,'IRREGULAR REGRESSION EFFECT FACTORS (X100)',/)(//,2x,'OTHER REGRESSION EFFECT FACTORS ', 'IN SA SERIES (X100)',/)(//,2x,'TRANSITORY REGRESSION EFFECT FACTORS',/)(//,2x,'FINAL DECOMPOSITION',/,2x,'-------------------')(//2x,'SEPARATE REGRESSION EFFECT FACTORS (X100)',/)(//,2X, 'FINAL SA SERIES WITH REVISED YEARLY',/)(//,2X,'FINAL SEASONAL FACTORS',/)FINAL TD FACTORSFINAL TRANSITORY FACTORS(//,2x,'FINAL TRANSITORY-IRREGULAR COMPONENT',/)(//,2X,'FINAL IRREGULAR FACTORS',/)Y@wJ?|=:0yE>Y@ORIGINAL(UNCORRECTED)SERIESTREND-CYCLE SA SERIESSEPARATEREGRESSIONEFFECTSEASONALFACTORSCOMPONENTTDfinal.-IRREG.TRANS.-IRREG.1x)(//,2x,'SE : STANDARD ERROR OF THE OBSERVED ', 'SERIES FORECAST.'/,2x,'SER : STANDARD ERROR OF THE ', 'REVISION.',//,2x,'Note 1 : SINCE THE COMPONENT IS ', 'NEVER OBSERVED,THE FORECAST ERROR IS OF LITTLE',/,2x, 'APPLIED INTEREST. WHAT IS OF INTEREST ', 'IS THE SE OF THE REVISION THE FORECAST',/,2x, 'OF THE COMPONENT WILL UNDERGO (UNTIL IT BECOMES ', 'THE FINAL OR HISTORICAL ESTIMATOR).',/)(2x,'Note 2 : SER(Seasonal) = SER (SA Series)',/)|=Y@(//,6X,'ORIGINAL SERIES (from regARIMA)')(//,6X,'ORIGINAL SERIES')(//,6X,'FINAL SEASONALLY ADJUSTED SERIES')(//,6X,'SEASONALLY ADJUSTED SERIES')(//,6X,'FINAL TREND-CYCLE')(//,6X,'TREND-CYCLE')Y@(//,2X,'DECOMPOSITION OF VARIANCE (IN %)')(2X,'--------------------------------')(/,6x,'A) SAMPLE VARIANCE FOR ORIGINAL SERIES')(/,22X,'FINAL',12X,'STOCHASTIC',/)(4X,'SEASONAL',6X,F12.4,6X,F12.4)(4X,'COMPON.',/)(4X,'TREND-CYCLE',3X,F12.4,6X,F12.4,/)(4X,'IRREGULAR',5X,F12.4,6X,F12.4)(4X,A,4X,F12.4,6X,F12.4)(4X,'TOTAL',9X,F12.4,6X,F12.4,/)(4X,'SA SERIES',5X,F12.4,6X,F12.4)?(/,6X,'B) VARIANCE OF THE STATIONARY SERIES')(/,22x,'THEORETICAL',12x,'MMSE',12x, 'ESTIMATED')(22x,'COMPONENT',11x,'ESTIMATOR',10x, 'COMPONENT'/)(4X,'SEASONAL',6X,F12.4,8X,F12.4,7X,F12.4)(4X,'TREND-CYCLE',3X,F12.4,8X,F12.4,7X,F12.4,/)(4X,'IRREGULAR',5X,F12.4,8X,F12.4,7X,F12.4)(4X,A,4X,F12.4,8X,F12.4,7X,F12.4)(4X,'TOTAL',9X,F12.4,8X,F12.4,7X,F12.4/)(4X,'SA SERIES',5X,F12.4,8X,F12.4,7X,F12.4,//)Y@?@?(////, 2x,'SECOND ORDER MOMENTS OF THE (STATIONARY)', ' COMPONENTS ', 'OVER / UNDER ESTIMATION TESTS',/,2x, 81('-'))(//,4x,'1. VARIANCE',/,4x,11('-'),/)(6x, 'TREND-CYCLE',4x,a)(6x, 'SEASONAL',7x,a)(6x, A,2x,a)(6x, A,5x,a)(6x, 'IRREGULAR',6x,a)(//,4x,' ++ : Overestimation of component.', ' Strong evidence (t>3).')(4x,' + : Overestimation of component.', ' Mild evidence (23).')(4x,' + : Too much positive correlation.', ' Mild evidence (23).')(4x,' + : Too much positive crosscorrelation.', ' Mild evidence (2)333333?Q?333333ÿٿh㈵>ɿffffff????rqrq?tE]tѿ333333?tE]t?)\?)\\(\@\(\?\(\?{Κ?xTr?{GzvH7B-DT!@|{Tr?DT!@@@ansub5.f(///)(' SERIES TITLE: ',a)NOYES(1X,A,2X,A)PREADJUSTED WITH regARIMA :(I2,'-',I4,64(2X,G18.9))LONG TERM TRENDSA series without BCSeries without BC "(2x,'DATE',11x,A)Failed(A)(I2,'-',I4,64(6X,G18.9))(2A,2x,A,i3,2A)(Series in input file has been multiplied by 10**).(14x,A)Series(10x,A)TrendCycle(2x,A)RealTimeTrendCycle(11x,A)SA SeriesRealTime SA Series(7x,A)Y. Revised SA(12x,A)SeasonalCalendarIrregularfinalTDTransitoryPreadjust(15x,A)Cycle(5x,A)(13x,A)E-Resid(6x,A)Sep. REG Comp.(4x,A)REG Comp. in SAStoch TrendCycleStoch. SASeriesiTREND-CYCLESEASONALTRANSITORYSEASONALLY ADJUSTED SERIES(//,2X,"*******************************")(2x,"TO PROVIDE A BETTER FIT, SEATS",/,7x, "HAS CHANGED THE MODEL")(2X,"*******************************",/)(2x,"TO FIT BETTER THE SERIES, SEATS",/,7x, "HAS CHANGED THE MODEL")(2x,"TO FIT BETTER THE SERIES, SEATS",/,7x, "HAS CHANGED THE MODEL")x,??vIh%<=|=?ansub8.fSCRATCH6572012/11/28 12:09:23Revision: Build: old(2x,'*** Seats Build date :',A,' ***')00-0000all(f18.0){XConstant8 inputansub9.flamimeanbpbdbqsqgmqbthiqmmaxitepsivepsphifhnoseriepgmodelsummxlnoadmissoutnastochtdcrmeaniterbiastramonoutrnouirneastnpatdnpareginterprsaqmaxrmodbthlimharfortrblqttmuhplanhpcyclerogtablestatseaskunitsacfeposbphinousnochmodelprintphtrfcentrregstabtablespsieinicpsiefinfirstobslastobshppermaxspectbrolblamdabseriebmidbcmarkodateolendetseasndsnfixed?K 8(a,i2,a2,1x,a,',',i4,' to ',i2,a2,1x,a,',',i4)modelspan: (a,i4,' to ',i4)periodoutlierspan: tdlomeasteruser(a:,a)aictest: noneTransformed (prior-adjusted) data for regARIMA modeling?Data()(/,' MODEL IDENTIFICATION (Using regression residuals)')(/,' MODEL IDENTIFICATION')Regression ModelRegression Model (fixed)automodeltype: automdl(a,e15.8)bautomd:bautomd.diag:eautomd:eautomd.diag:no (2x,'Number of forecasts/backcasts set to zero because ', 'forecast error for the',/, 2x,' model identified, ',F10.3,', is greater than ',f10.3, '.')yesrejectfcst: (a,f12.4)fcstlim: mape3yr: fcstrejected: (a,f6.3,1x,a)aocrit: lscrit: tccrit: (a,f10.6)reducecv: automdl: ('arimamdl: ',a)(a,i6)maxiter: (a,e13.6)tol: (5x,'Automatic model chosen : ',a,/)pickmdlautomdl(default): (5x,'Default model used : ',a,' (no model selected)',/)aictest.pv: selected ERROR: Cannot perform seasonal adjustment if the automatic model selection procedure cannot select an ARIMA model and missing value regressors are part of the model.none(/,' MODEL DEFINITION')(0 0 0)E:(//,' MODEL ESTIMATION/EVALUATION') estimatedERROR: An model estimation error has occurred during the AIC testing of trading day regressor(s). The error message appears below. lom/loq/lpyear regressor(s). The error message appears below. an Easter regressor. The error message appears below. user defined regressor(s). The error message appears below. All user-defined regressors deleted; no chi-square testing will be performed.ERROR: An model estimation error has occurred during the testing of a user-defined holiday regressor. The error message appears below.bidotlr:bidotlr.diag:eidotlr:eidotlr.diag:(/,2x,'The following sequence outliers have been ', 'deleted since the',/, 2x,'absolute value of their t-values are less than ', f10.3,':')(5x,a,' (t-value = ',f10.3,')')(/,2x,'regARIMA model will be restimated without these ', 'regressors.',/)(' Average Absolute Percentage Error : ',a)out-of-sample forecastswithin-sample forecasts(' AAPE(Last year) : ',f16.2,/, ' AAPE(Last-1 year) : ',f16.2,/, ' AAPE(Last-2 year) : ',f16.2,/, ' AAPE(Last 3 years): ',f16.2)(a)aape.mode: outofsampleaape.mode: withinsampleaape.0: aape.1: aape.2: aape.3: aape.mode: none(/,' WARNING: Convergence of the coefficient estimation ', 'procedure required',/, ' more than ',i3,' iterations. This often ', 'indicates some inadequacy',/ ' in the model being estimated.',/) NOTE: Fixed values have been assigned to some regression and ARIMA model coefficients. If these values are estimates calculated by X-13ARIMA-SEATS, then the model comparison statistics (AIC, AICC, Hannan Quinn, and BIC) and the P-values of the Q's of the sample autocorrelations of the residuals below are invalid and should not be used. NOTE: Fixed values have been assigned to some regression coefficients. If these values are estimates calculated by X-13ARIMA-SEATS, then the model comparison statistics (AIC, AICC, Hannan Quinn and BIC) below are invalid and should not be used.loglikelihood: aic: aicc: bic: hq: eic: k: AIC : AICC : BIC : Hannan-Quinn : (a,f6.2,a,f12.4) EIC (k=) : Regression MatrixModel ResidualsTM(//,' DIAGNOSTIC CHECKING')L(' Histogram of the Standardized and Mean-Centered', ' Residuals')(/,' Normality Statistics for regARIMA Model Residuals:')(/,' Durbin-Watson Statistic for regARIMA Model Residuals:')(2x,a,' = ',f12.6)dwDurbin-Watson statisticdurbinwatson: (/,' Friedman Non-Parametric Test for regARIMA Model', ' Residuals:')(2x,a,' = ',f12.6,' ( Asymptotically distributed as ', 'Chi-Square(',i2,'), P-Value = ',f12.6,' )')ken(a,e15.8,1x,i3,1x,e15.8)friedman: Friedman test(/,' QS Statistic for regARIMA Model Residuals (',a,'):', t65,f10.2,/,t56,'(P-Value = ',f10.4,')')full seriesstarting ]Regression EffectsERROR: Additive seasonal adjustment will not be performed when preadjustment factors are derived from a REGARIMA model for transformed data. Check the values for the power or function arguments of the transform spec and mode of the x11 spec.ERROR: Multiplicative or log additive seasonal adjustment cannot be performed when preadjustment factors are derived from a regARIMA model for data which have not been log transformed.Trading DayStock Trading Day1-Coefficient Trading Day1-Coefficient Stock Trading Dayfinalreg(a,i2)nfinalreg: finalreg01:arima.farmacr.f(/,' ARMA Parameter Correlation matrix',/,' Parameter', (:t15,10I6))(' ',(78a))- (' ',a,t39,a)(' Lag',i3,5x,10F6.2,(:/,t14,10F6.2))$ERROR: The covariance matrix of the ARMA parameters is singular; cannot compute t-statistics for the ARMA parameters.PERT! @?automd.f(50x,'Automatic ARIMA Model Selection',//, 30x,'Procedure based closely on TRAMO method of Gomez', ' and Maravall (2000)',/, 39x,'"Automatic Modeling Methods for Univariate Series",',/, 30x,'A Course in Time Series (Edited by D. Pena, G. C. ', 'Tiao, R. S. Tsay),',/, 50x,'New York : J. Wiley and Sons',//)(24x,'Automatic ARIMA Model Selection',//, 20x,'Procedure based closely on TRAMO method ',/, 25x,'of Gomez and Maravall (2000)',/, 14x,'"Automatic Modeling Methods for Univariate Series",',/, 28x,'A Course in Time Series',/, 18x,'(Edited by D. Pena, G. C. Tiao, R. S. Tsay),',/, 25x,'New York : J. Wiley and Sons',//)(' Maximum order for ',a,' : ',i3)regular ARMA parametersseasonal ARMA parametersregular differencingseasonal differencing(' ',a,' set to ',i3)Regular differencingSeasonal differencing(5x,'Default model will be accepted if residuals pass ', 'Ljung-Box test')(a,2i5)maxorder: maxdiff: diff: (a,a)acceptdefault: yesnocheckmu: balanced: mixed: exactdiff: firstNOTE: Tables associated with the outlier spec cannot be saved during automatic model selection. Checking 8ConstantERROR: A model estimation error has occurred during AIC testing within the automatic model identification procedure. The error message appears below.(/,' ERROR: Estimation failed to converge during the ', 'automatic model', /,' identification procedure.')automdl.first: (//,' Final Checks for Identified Model',/)(/,' ',a) Checking for Unit Roots.(3x,a,' unit ',a,' found.')Regularroot(' ',2(' (',i2,',',i2,',',i2,')'))SeasonalNoroots(' Unit roots in final model : ',a)nonenonseasonalseasonalnonseasonal seasonalfinalur: Checking for nonseasonal overdifferencing.(' ',a) Reduce order of nonseasonal MA, nonseasonal differencing. Add constant term.NOTE: Due to a reduction in the order of regular differencing, a constant term should be added to the regARIMA model. Either rerun the spec file with checkmu = yes in the automdl spec, or add a constant regressor to the regARIMA model via the regression spec.(3x,'Nonseasonal MA not within ',f6.3, ' of 1.0 - model passes test.')MbP? T-statistic for residual mean > 2.5; Checking for Constant term. constant term added to identified model. constant term not added to identified model since checkmu=no in input specification file. for insignificant ARMA coefficients.(/,A,1X,F12.3/)Critical Value for AO outlier CHANGED TO:Critical Value for LS outlier CHANGED TO:Critical Value for TC outlier CHANGED TO:(/,3x,'More than one ARMA coefficient was found to be ', 'insignificant.') Since no outlier were found, model will be changed to and automatic outlier identification will be redone. Identification of model and/or differencing order will be redone. Due to insignifcant ARMA coefficients, model changed to(/,' Final automatic model choice : ',a) automean: no testing performednocheckconstant specified in modeluserspecified(/,a,' significant.')automean: isautomean: not(a,i5)idnonseasonaldiff: idseasonaldiff: End of automatic model selection procedure.@ffffff@NOTE: Tables associated with the outlier spec cannot be saved during automatic model selection.ERROR: Must have user supplied models stored in .(/,' Autoregressive Integrated Moving Average (ARIMA) ', 'extrapolation program',/,' ARIMA extrapolation', ' model (forecast)',/)(' Model selected: First model that meets ', 'acceptance criteria.')(' Model selected: Model with lowest average ', 'forecast error that',/,' meets acceptance criteria.')(5X,'Autoregressive Integrated Moving Average (ARIMA) ', 'extrapolation program',/,' ARIMA extrapolation', ' model (forecast)',/)(/,5x,'Model selected: First model that meets acceptance', ' criteria.')(/,5x,'Model selected: Model with lowest average ', 'forecast error that meets',/,21x,'acceptance criteria.')(a,': ',a)pickfirstyesnoidfirstmdlfilemdlfilename(a,': ',f12.6)fcstlimitbcstlimitqlimoverdiff()QP(/,' ERROR: No ARIMA models stored in ',a,'.', /,' Check contents of file and try again.')(/,' WARNING: Unable to process at least one of the ARIMA', ' models stored in ',/,' ',a,'.',/, ' Check contents of this file and try again.')(/,' WARNING: Estimation errors occured during the ', 'automatic model ', /,' selection procedure. For more details, ', 'check error file ', /,' ',a,'.err ')(//,15x,'None of the models were chosen.',/)none(/,' ERROR: Unable to read automatic model for the ', 'reason(s) given above.',/, ' Check the models stored in ',a,'.')(/,' NOTE: Default model already specified.',/, ' Check the model file ',a,'.')ERROR: An model estimation error has occurred during the AIC testing of trading day regressor(s). The error message appears below. lom/loq/lpyear regressor(s). The error message appears below. an Easter regressor. The error message appears below. user defined regressor(s). The error message appears below.ERROR: An model estimation error has occurred during the chi square testing of user defined holiday regressor(s). The error message appears below.(' Rerun program trying one of the following:',/, ' (1) Allow more iterations (set a larger ', 'value of maxiter).')(' (2) Remove model from automatic model ', 'file',1x,a,'.')(' (2) Use an automatic model file to specify ', 'other models.')(' See ',a,' of the ',a,' ',a,' for more',/, ' discussion.')X-13ARIMA-SEATS(' Estimation errors associated with the model: ',a)(/,' WARNING: Estimation error encountered for default ', 'model.',/,' Default model will not be used.')8Seasonal MANonseasonal MA(' WARNING: The seasonal MA coefficient(s) for at least', ' one of the models',/, ' tested above have a sum exceeding ',f6.3,'.', //,' Examine whether a differencing can be ', 'eliminated from the',/, ' regARIMA model in favor of a trend constant ', 'in the regression',/, ' spec, or whether a seasonal differencing ', 'should be replaced',/, ' by the use of fixed seasonal effects in the ', 'regression spec.')ERROR: A model estimation error has occurred during the AIC testing of(15x,'A default model specified by the user, ',a,',',/, 15x,'will be used to generate regARIMA preadjustment ', 'factors')(//,15x,'The model chosen is ',a,/)(5X,'Autoregressive Integrated Moving Average (ARIMA) ', 'extrapolation program',/,7x,'ARIMA extrapolation model ', '(backcast)',/)(//,15x,'This model was not chosen for backcasting.',/)automx.f?NOTE: Cannot generate plot since expected value of average not in plotting range.User-defined045bench.f/series/graph.lstoldappend(A)8QPK T7 P  Q P  Qbtrit.f(' S 3.',a2,' Breakdown of Average Maximum Absolute ', 'Differences across spans for ',a,/,10x,'of ',a,'.',/)(' S 3.',a2,' Breakdown of the Average Maximum ', 'Absolute Differences across spans for ',/,10x,a,' of ', a,'.',/)(/,' S 3.',a2,' Breakdowns of unstable ',a, ' and Average Maximum Percent Differences', /,10x,'across spans for ',a,' of ',a,'.',/)(/,' S 3.',a2,' Breakdowns of unstable ',a,/,10x, 'and Average Maximum Percent Differences across ', 'spans for ',/,10x,a,' of ',a,'.',/)(' S 3.',a2,' Breakdown of Average Maximum Percent ', 'Differences across spans for ',a,/,10x,'of ',a,'.',/)(' S 3.',a2,' Breakdown of the Average Maximum ', 'Percent Differences across spans for ',/,10x,a,' of ', a,'.',/)(10x,'Indirect seasonal adjustment',/)(10X,A9,A3,I3,5X,A8,F5.1,a)(10X,A9,A3,F6.2)(10X,A9,A3,I3,5X,A8,F.1,a)(10X,A9,A3,F.2) : (AMPD = )(/)(10X,I4,5X,A3,I3,5X,A8,F5.1,a)(10X,I4,5X,A3,F6.2)(10X,I4,5X,A3,I3,5X,A8,F(10X,I4,5X,A3,F('s3.',a,'.brk.p',i2.2,': ',A3,1x,I3,2X,E17.10)('s3.',a,'.brk.y',i2.2,': ',I4,1x,I3,2X,E17.10)@@?Y@??V@@D63E??WARNING: regARIMA preadjustment factors are only produced for either the log or no transformation.K chitst$User-defined Holiday Regressorschkchi.f(//,' User-defined Holiday Regression groups removed (at ', f12.6,' percent level):')(5x,a)(//,' No User-defined Holiday Regression groups removed.')Y@$@8@1@Constant8ERROR: A model estimation error has occurred during testing for a constant term within the automatic model identification procedure. The error message appears below.chkmu.f(/,' NOTE: Cannot perform test for constant term:',/, ' Model estimation does not converge when ', 'constant term added.',//, ' Constant term will not be included in regARIMA', ' model',/)(' Constant term removed from model')PQchkorv.f(4x,a,t21,a,t36,a)added(a,a,a,a,a)?{Gz?? roots inside the unit circle. Will attempt to invert them.chkrt2.f(' ',a,' Roots',/,' Root',t25,'Real',t31,'Imaginary', t44,'Modulus',t53,'Frequency',/,a)(' Root',i3,t18,4F11.4)?chksmd.f(/,' NOTE: The SEATS signal extraction routines cannot', ' process more than ',i3,/,' ',a,' terms.',/, ' The program will stop executing; try specifying', ' another ARIMA model.',/)Nonseasonal ARNonseasonal MA(/,' NOTE: The SEATS signal extraction routines cannot', ' process missing lag models.',/, ' The program will stop executing; try specifying', ' another ARIMA model.',/)Seasonal ARSeasonal MAchktrn.f(/,' WARNING: At least one negative value was found in', ' one of the trend', /,' cycle estimates (',a,i3,'). Negative ', 'value(s) will be replaced', /,' either by the mean of its two closest ', 'neighbors that are greater', /,' than zero, or by the nearest value that ', ' is greater than zero', /,' (if the value is on either end of the ', 'series).')(/,' These are often caused by poor forecasts ', 'and/or backcasts.', /,' Users should check the fit of any existing', ' regARIMA model,', /,' using the diagnostics in the check spec.')(/,' These are often caused by substantial ', 'outliers in the original', /,' series, or poor forecasts and/or ', 'backcasts. Users should', /,' fit a regARIMA model to the series using ', 'outlier regression', /,' variables to correct for such effects, and', ' check the fit of', /,' any existing regARIMA model, using the ', 'diagnostics in the', /,' check spec.')(/,' These are often caused by substantial ', 'outliers in the original', /,' series. Users should fit a regARIMA ', 'model to the series', /,' using outlier regression variables to ', 'correct for such effects.')@chsppf.f(' ***** FATAL ERROR--THE FIRST INPUT ARGUMENT TO THE ', 'CHSPPF SUBROUTINE IS OUTSIDE THE ALLOWABLE (0,1) INTERVAL ', '*****')(' ***** THE VALUE OF THE ARGUMENT IS ',E15.8,' *****')(' ***** FATAL ERROR--THE SECOND INPUT ARGUMENT TO THE ', 'CHSPPF SUBROUTINE IS NON-POSITIVE *****')(' ***** THE VALUE OF THE ARGUMENT IS ',I8 ,' *****')(' *****ERROR IN INTERNAL OPERATIONS IN THE CHSPPF ', 'SUBROUTINE--THE NUMBER OF ITERATIONS EXCEEDS ',I7)(' THE INPUT VALUE OF P IS ',E15.8)(' THE INPUT VALUE OF NU IS ',I8)(' THE OUTPUT VALUE OF PPF HAS BEEN SET TO 0.0')?@$@?|= _B?4All User-defined Holiday Regressorschi$?RegressorsTrading Day + Leap Year + Length of Quarter + Length of Month (Combined Trading Day and Leap Year and Length of Quarter and Length of Month User-defined Trading Day Combined Trigonometric Seasonal RegressorsUser-defined Seasonal RegressorsUser-defined RegressorsAll User-defined RegressorsabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZcncrnt.f(1x, 'p =', i3, 1x, 'ps =', i3, 1x, 'pn =', i3, 1x, 'q =', i3, 1x, 'qs =', i3, 1x, 'qn =', i3, 1x, 'variance ratio for s =', f12.6, 1x, 'variance ratio for n =', f12.6)(/1x, 'phis coefficients',1x, 50(f21.15))(/1x, 'phin coefficients',1x, 50(f21.15))(/1x, 'thetas coefficients',1x, 50(f21.15))(/1x, 'thetan coefficients',1x, 50(f21.15))(/1x, 'theta coefficients',1x, 50(f21.15)),X-DT! @@Nonseasonal ARSeasonal ARNonseasonal MASeasonal MAcoladd.f(/,' ERROR: Invalid column information: Beginning ', 'column of the insertion',/, ' must be between 1<=begcol<=ncxy+1',/, ' 1<=',i4,'<=',i4,'.')(/,' ERROR: nrxy*(noldc+naddc)=',i4,'*(',i4,'+',i4,')>', i6,'.') combft.f()(/,a, 'COMBINED TEST FOR THE PRESENCE OF IDENTIFIABLE SEASONALITY')(/,a,'IDENTIFIABLE SEASONALITY PRESENT')(/,a,'IDENTIFIABLE SEASONALITY PROBABLY NOT PRESENT')(/,a,'IDENTIFIABLE SEASONALITY NOT PRESENT')"@@@?@@? minmax@cormtx.f(/,' Correlation matrix',/,' Variable',(:t20,10I6))(' ',(78a))-(' ',a,t20,10F6.2)(t20,10F6.2)corplt.f(17x, '-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.0')(17x,' +',10('----+')) (/,' ERROR: Sample ACF or PACF computations', ' produced values greater than one in norm.')(10x,i3,4x,a2,51A1,f6.3)(a)?I@??0123456789eEdD^$@0123456789 JanFebMarAprMayJunJulAugSepOctNovDec0123456789?,cvdttm.f(4x,a3,4(1x,i2),1x,i4)(1x,a3,1x,i2,', ',i4,2x,2(i2.2,'.'),i2.2,1x)cvrerr.f(' ERROR: ',a,' start date, ',a, ', must begin on or after ',/,' ',a, ' start date, ',a,'.',/)(' ERROR: ',a,' end date, ',a,', must end on or before ',/, ' ',a,' end date, ',a,'.',/)(' ERROR: ',a,' end date, ',a,', must end after ',/, ' its own start date, ',a,'.',/)$@Index out of range vectordeltst.f(/,' ERROR: Cannot compute outlier t-statistic for', ' outlier backward deletion - ', /,' the residual root mean square error is zero.')(/,' Check the x11regression options specified', ' in the input specification',/,' file.',/)(/,' Check the regARIMA model specified in the', ' input specification',/,' file.',/)P desreg.f(/,' ',a) (a) + ?O63E?vIh%<=dlrgef.f(/,' ERROR: Deleted columns,',i3,':',i2,', not within',i3, ' column regression matrix.')Pdlusrg.f(/,' ERROR: Deleted column,',i3,' not within',i3, ' column user-regression matrix.')4)ơ;?dsarma.f(' ',a,': ',a)(0 0 0)(/,' ',a,/,' ',a)dtoc.f(/,' ERROR: Cannot write ',a,' in ',i3,' spaces.',/) ('(1x,a,t',i2,',a,1x,f15.4)')EasterStatCanEasterStockEaster(//,' Likelihood statistics for model without Easter')(//,' Likelihood statistics for model with ',a)AICC(no easter):('aictest.e.aicc.',a,': ',e29.15)noeasterAICC()('aictest.e.aicc.',a,i2.2,': ',e29.15)easter8(//,' ***** AICC (with aicdiff=',F7.4, ') prefers model without Easter *****')(//,' ***** AICC (with aicdiff=',F7.4, ') prefers model with ',a,'[',i2,'] *****')Stock EasterStatistics Canada Eastereasaic.fi@$@?8@9@1@&@,@@5@@Y@8WARNING: The program will not generate backcasts for series with a modelspan that starts after the start of the span.WARNING: The program will not generate backcasts for use with SEATS seasonal adjustments.NOTE: A longer forecast horizon is required by the SEATS signal extraction procedure, so the number of forecasts generated by this run has been changed to . MVMissing ValueERROR: Missing value code found outside of model span, where missing value cannot be replaced.WARNING: Automatic transformation selection cannot be done on a series with zero or negative values.ERROR: Pseudo-additive seasonal adjustment cannot be done on a series with negative values.ERROR: Multiplicative or log-additive seasonal adjustment cannot be done with a series with zero or negative values.?ERROR: All data values for at least one month are missing values.ERROR: All data values for at least one quarter are missing values.ERROR: All data values for at least one period are missing values. regARIMA model cannot be estimated.(' WARNING: For ',i2,1x,a,' the number of missing ', 'values for the ',a,' is',/, ' greater than the number of data values ', 'specified.',//, ' The missing value replacement procedure ', 'used by ',a,/, ' cannot be considered optimal for this ', 'situation, and the user',/, ' should consider other methods of missing ', 'value replacement.')monthsmonthX-13ARIMA-SEATSquartersquarterperiodsperiodERROR: All data values read into X-13ARIMA-SEATS are equal to zero.WARNING: All data values read into X-13ARIMA-SEATS are the same.NOTE: At least one value that is either less than or equal to zero or equal to the missing value code was found after the span of data to be analyzed, but within the time frame of the forecasts generated by the regARIMA model. In this situation, the forecast output will not include a comparison of the forecasts with the corresponding values of the original series. comparison of the transformed forecasts with the corresponding values of the transformed original series.ERROR: Must specify a regARIMA model when the Missing Value procedure is used.ERROR: Cannot specify irregular component regression with a regARIMA model when the Missing Value procedure is used.ERROR: Length of forecast augmented series () exceeds program limit (). See Section 2.7 of the Reference ManualUERROR: Number of years spanned by the forecast augmented series () exceeds program limit ( Reference Manual.ERROR: Series to be modelled and/or seasonally adjusted must have at least 3 complete years of data.ERROR: Cannot specify prior adjustment factors when automatic transformation selection is used.ERROR: Cannot specify fixed regression coefficients when automaticERROR: Additive seasonal adjustment will not be performed when the prior adjustment factors are expressed as percentages.ERROR: Cannot combine prior adjustment factors expressed as differences with prior adjustment factors expressed as percentages.ERROR: Leap Year prior adjustment (adjust=lpyear) can only be specified when a log transformation is specified in the transform spec. when a multiplicative seasonal adjustment isspecified in the x11 spec.ERROR: Length of month prior adjustment (adjust=lom) can only be specifiedERROR: Length of quarter prior adjustment (adjust=loq) can only be specifiedERROR: Length of month prior adjustment (adjust=lom) cannot be specifiedERROR: Length of quarter prior adjustment (adjust=loq) cannot be specified when an additive seasonal adjustment is specified in the x11 spec.ERROR: Leap year prior adjustment (adjust=lpyear) cannot be specified when td or td1coef is specified in the variables argument of the x11regression spec.Trading Day1-Coefficient Trading DayLength-of-MonthLength-of-QuarterLeap YearStock Trading Day1-Coefficient Stock Trading DayERROR: Need monthly data to perform aictest for stock trading day.ERROR: Need monthly or quarterly data to perform aictest for trading day.ERROR: Cannot generate trading variables for aictest before 1776. Either specify a starting date, or include the century in the start or modelspan arguments of the series spec.(/,' ERROR: Cannot perform an AICtest for ',a,/, ' regressors on a ',a,' time series.')stock trading dayflowstock 1-coefficient trading daystock 1-coefficient trading dayflow trading daystockflow 1-coefficient trading dayflow 1-coefficient trading daytdtdnolpyeartdstocktd1coeftd1nolpyeartdstock1coef(/,' ERROR: ',a,' was specified in the variables argument ', 'of the regression')(' spec but ',a,' is given in the aictest argument.') The type of trading day regressor must agree.[ERROR: Can't specify a length of month, quarter, or leap year variable when using the td option of aictest. using the td1coef option of aictest.(/,' ERROR: ',a,' prior adjustment (adjust=',a,') cannot ', 'be specified')Length-of-monthlomLength-of-quarterloq(' when ',a,' is given in the aictest argument ', 'of the ',a,/, ' spec.',/)regressionLeap yearlpyeartdstock The type of regressor must agree.ERROR: AIC test for the length of month regressor cannot be specified whenERROR: AIC test for the length of quarter regressor cannot be specified when the td or td1coef option is given in the aictest argument.ERROR: AIC test for the leap year regressor cannot be specified when the td or td1coef option is given in the variables argument and a power transformation is performed.ERROR: AIC test for the leap year regressor cannot be specified when stock trading day is specified in the regARIMA model. stock trading day is specified as a user defined regressor.stock Eastereastersceastereasterstock The type of Easter regressor must agree.NOTE: Stable seasonal regressors present in the regARIMA model. Maximum seasonal difference in automatic model identification procedure set to zero. Seasonal difference in automatic model identification procedure set to zero.EasterStatCanEasterStockEasterPERROR: Must use end-of-month stock trading day with current stock Easter regressor. Specify tdstock[31] in the variables argument of the regression spec.ERROR: Need monthly or quarterly data to perform aictest for Easter.ERROR: Cannot generate Easter variables for aictest before 1901.ERROR: Cannot generate Easter variables for aictest after 2100.ERROR: Prior Trading Day weights cannot be less than zero for a multiplicative seasonal adjustment.ERROR: Prior Trading Day weights cannot be specified when automatic transformation selection is performed.ERROR: Prior Trading Day weights can only be specified for a multiplicative or log-additive seasonal adjustment.ThanksgivingLaborERROR: Stock trading day and holiday irregular component regression variables cannot be specified in the same run.ERROR: Cannot specify fixed coefficients for the trading day regressors that imply daily weights less than zero w hen specifying reweight=yes in the x11regression spec.NOTE: Cannot reweight trading day coefficients if all trading day regressors are fixed; reweighting of daily weights will not be performed.ERROR: Cannot specify fixed coefficients for stock trading day regressors in the x11regression spec that produce a nonpositive trading day factor. Use the regression spec to estimate the stock trading day effect.AOERROR: The sigma argument of the x11regression spec can only be specified when flow trading day variables are the only regressors in the irregular regression.ERROR: A stocktd regressor has been specified in the variables argument of x11regression but td1coef is given in the aictest argument.ERROR: A td or td1coef regressors has been specified in the variables argument of x11regression but tdstock is given in the aictest argument. ERROR: A td regressor has been specified in the variables argument of x11regression but td1coef is given in th e aictest argument. (before (change for before (starting (change for after tdtdstocktd1coeftdstock1coefx11regressionERROR: Irregular component regression and regARIMA model-based trading day adjustment cannot be specified in the same run.ERROR: Irregular component regression and regARIMA model-based holiday adjustment cannot be specified in the same run.NOTE: An X-11 holiday adjustment cannot be performed when a user-defined mean is specified for the irregular regression.ERROR: Cannot calculate X-11 holiday adjustment for a quarterly series.ERROR: An X-11 holiday adjustment cannot be performed when the automatic transformation selection option is chosen.ERROR: An X-11 holiday adjustment cannot be performed unless the multiplicative seasonal adjustment option is chosen.ERROR: X-11 and regARIMA model-based Easter adjustment cannot be specified in the same run.ERROR: X-11 and irregular component regression-based Easter adjustment cannot be specified in the same run.ERROR: No X-11 holiday effect before 1901. Try including the century in the start dateERROR: Must remove both trading day and holiday from final seasonally adjusted series when user-defined mean is present.ERROR: Negative prior adjustment factors cannot be used for aERROR: The series must have at least five complete years to force the yearly totals of the seasonally adjusted series.ERROR: Cannot specify a seasonal filter when type=trend.WARNING: The program will not use a 3x15 seasonal filter for series shorter than 20 years.WARNING: The program will not use a 3x15 seasonal filter for serieseERROR: Length of Henderson filter cannot exceed ERROR: Length of Henderson filter must exceed 1.ERROR: Not enough observations in the series to apply a Henderson filter of length ERROR: I/C ratio cannot be specified when the automatic trend filter option is used.WARNING: Length of sliding span must be at least 3 years. Sliding spans analysis will not be performed.ERROR: Component series to be aggregated has a different time span. Aggregation will not be computed.WARNING: Cannot save iteration iformation for regARIMA model estimation when automatic modeling, AIC tests, or automatic transformation selection is used.NOTE: Since X-11 seasonal adjustment is not done, the forecast error will not be checked after the ARIMA model is identified.NOTE: Since X-11 seasonal adjustment is not done, the E1 table is not available. The B1 table will be used for the spectrum of the original series.ERROR: Pseudo-additive seasonal adjustment cannot be performed when preadjustment factors are derived from a REGARIMA model.ERROR: Pseudo-additive seasonal adjustment and irregular component calendar adjustment cannot be specified in the same run.ERROR: Cannot use prior adjustment factors in a pseudo-additive seasonal adjustment.WARNING: Pseudo-additive seasonal adjustment will not produce forecasts of the final seasonal difference unless regARIMA forecasts are used to extend the series. The regARIMA model used to extend the series cannot include regressors that result in preadjustment factors (such as outlier, trading day or holiday regressors) when pseudo-additive seasonal adjustment is used. If your model has such regressors, use the noapply argument of the regression spec.NOTE: The maximum regular ARIMA order that the automatic model selection procedure will identify has been changed to three (3) since SEATS seasonal adjustments are generated in this run..udgUNKNOWNseasonal adjustment and modeling diagnosticsuser specified metadata(/,' NOTE: The ',a,' ',a,' file (.udg) ', 'has been stored', 'stored', /,' in the directory specified by the graphics ', '(-g) option.')diagnosticmetadata(' Storing any ',a,' into ',a,/)diagnostics output(a)(/,' WARNING: Existing files will be overwritten by ', 'this run of ',a,'.',/,10x, 'A complete listing of all the files produced by this', ' run ',/,10x,'can be found in ',a,'.err')(/, ' FILE SAVE REQUESTS (* indicates file exists and will be overwritten)')(' ',a,a,' ',a).outprogram output file.errprogram error fileseasonal adjustment and model diagnostics file.gmtgraphics metafile.spcinput specification file(/,5x,'Contents of spc file ',a,//,' Line #',/,' ------')(a120)(1x,i6,': ',a)(/,5x,'Contents of model file ',a,//,' Line #',/, ' ------') No seasonal adjustment this runERROR: No tables were specified for printing or saving.ERROR: The aictest argument can only be specified when the model is estimated using maximum likelihood estimation.ERROR: Exact maximum likelihood estimation must be selected when AIC tests, automdl, or automatic transformation selection is used. editor.f@eltlen.f(' ERROR: No position',i3,' in ',i3, ' long character vector.')']C)ơ;?',i3,'.') old Reading from NEWnew(/,' ERROR: ',a,' ',a,' already exists.',/)(/,' ERROR: Unable to open ',a,', ',a,'.',/)??fstop.f ftest.f(' WARNING: Program cannot perform F-test on first ', 'differenced data.')(/,a,'Cannot compute F-statistic since residual mean', ' square error',/,a,'is equal to zero for this series.') WARNING: ()(a,'Test for the presence of seasonality assuming ', 'stability.',/)(a,'Sum of squares',2x,'Dgrs.freedom',2x,'Mean square',5x, 'F-value',/,a,f17.4,i9,f17.5, f12.3,a2,/,a,'Residual',f17.4,i9,f17.5,/,a,'Total',f17.4, i9,/) Between months Between quarters(a,'Sum of',5x,'Dgrs.of',9x,'Mean',/,a,'Squares',5x, 'Freedom',8x,'Square',7x,'F-Value',/,a,a,f17.4,i9,f17.5, f12.3,a2,/,a,'Residual',f17.4,i9,f17.5,/,a,'Total',f17.4, i9,/) Between monthsBetween quarters(a,a2,'Seasonality present at the 0.1 per cent level.')(a,A2, 'No evidence of stable seasonality at the 0.1 per cent level.')(/,a,'Due to the small residual mean square error all', ' the analysis', /,a,'of variance tests for this series may be invalid.')(/,a,'Test for the presence of residual seasonality.')(/,18X,A2, 'No evidence of residual seasonality in the entire series at the 1 per cent level. F =',F10.2)(/,5X,A2,'No evidence of residual seasonality in the ', 'entire series at the',/,12x,'1 per cent level. F =', F10.2)(/,18X,A2, 'Residual seasonality present in the entire series at the 1 per cent level. F =',F10.2)(/,5X,A2,'Residual seasonality present in the entire ', 'series at the',/,12x,'1 per cent level. F =',F10.2)(a,2(2x,f12.5))d11.f: id11.f: (/,18X,A2,'Residual seasonality present in the last 3 ', 'years at the 1 per cent level. F =',F10.2)(/,5X,A2,'Residual seasonality present in the last 3 ', 'years at the',/,12x,'1 per cent level. F =',F10.2)(/,18X,A2, 'No evidence of residual seasonality in the last 3 years at the 1 per cent level. F =',F10.2)(/,18X,A2, 'Residual seasonality present in the last 3 years at the 5 per cent level.')(/,18X,A2, 'No evidence of residual seasonality in the last 3 years at the 5 per cent level.')(/,5X,A2,'No evidence of residual seasonality in the ', 'last 3 years at the',/,12x,'1 per cent level. F =', F10.2)(/,5X,A2,'Residual seasonality present in the last 3 ', 'years at the',/,12x,'5 per cent level.')(/,5X,A2,'No evidence of residual seasonality in the ', 'last 3 years at the',/,12x,'5 per cent level.')d11.3y.f: id11.3y.f: (/,1X,'Note: sudden large changes in the level of the ', 'adjusted series will invalidate the results ', 'of this test for the',/,50x,'last three year period.')(/,1X,'Note: sudden large changes in the level of the ', 'adjusted series will',/,7x,'invalidate the ', 'results of this test for the last three year period.')?Y@?{Gz?@V@D@??@?@@?3gXܟ#?/5|>րcJ.F?(V?7 J?VD$`?0z?]pOOOsO"OOxO Invalid date, seasonal period of data not annual.Invalid date, no period for nonseasonal dataInvalid date, seasonal period of data not monthly.Invalid date, expected a monthly abbreviationNot a valid date - remove quotes.Not a valid datetime series data (for the span analyzed)original seriesinput specification fileoriginal series adjusted for missing value regressorsregARIMA calendar adjusted original dataregARIMA outlier adjusted original dataoriginal series (prior adjusted)original series (prior adjusted)time series data plus constant (for the span analyzed)original series plus constantprior-adjustment factorspermanent prior-adjustment factorstemporary prior-adjustment factorsprior-adjusted datapermanent prior-adjusted dataprior-adjusted data (including prior trading day adjustments)permanent prior-adjusted data (including prior trading day adjustments)prior-adjusted and transformed dataFmatrix of regression variablesregARIMA combined outlier componentregARIMA AO outlier componentregARIMA level change outlier componentregARIMA temporary change outlier componentregARIMA seasonal outlier componentregARIMA trading day componentregARIMA holiday componentregARIMA user-defined regression componentregARIMA user-defined seasonal componentregARIMA transitory componentregression trading day weightsresidual autocorrelations for different orders of differencingautocorrelation for different orders of differencingresidual partial autocorrelations for different orders of differencingpartial autocorrelation for different orders of differencingautomatic ARIMA model selectionmodel identification (forecast)model identification (backcast)detailed output for the estimation iterationsmodel specifications (regression and arima specs)correlation matrix of regression parameter estimatesregression and ARMA parameter estimatescorrelation matrix of ARMA parameter estimatesmaximized log-likelihood and model selection criteriaroots of the AR and MA operatorsestimated regression effects (X'beta)residuals from the estimated modelresiduals from the estimated regression effectsoutlier detection results, by iterationoutlier AO and LS test statisticsfinal outlier test statisticsresidual autocorrelationsresidual autocorrelationresidual partial autocorrelationresidual partial autocorrelationsquared residual autocorrelationssquared residual autocorrelationhistogram of the regARIMA residualsnormality statistics for regARIMA residualsDurbin-Watson statistic for model residualsFriedman non-parametric test for residual seasonalitypoint forecasts and standard errors for the transformed dataforecast error variances (transformed scale)point forecasts and prediction intervals on the original scalepoint backcasts and standard errors for the transformed datapoint backcasts and prediction intervals on the original scale[spectrum of the original seriesspectrum of the regARIMA model residualsspectrum of differenced seasonally adjusted seriesspectrum of modified irregular seriesspectrum of the seasonally adjusted series (SEATS)spectrum of the irregular component (SEATS)spectrum of the extended residuals (SEATS)spectrum of differenced indirect seasonally adjusted seriesspectrum of indirect modified irregular componentspectrum of the composite seriesTukey spectrum of the original seriesTukey spectrum of the regARIMA model residualsTukey spectrum of differenced seasonally adjusted seriesTukey spectrum of modified irregular seriesTukey spectrum of the seasonally adjusted series (SEATS)Tukey spectrum of the irregular component (SEATS)Tukey spectrum of the extended residuals (SEATS)Tukey spectrum of differenced indirect seasonally adjusted seriesTukey spectrum of indirect modified irregular componentTukey spectrum of the composite seriesQS diagnostic to detect seasonalityPeak probabilties for the Tukey spectrumqmodified original data, C iterationmodified original data, D iterationoriginal data modified for extremesMCD moving averagepreliminary trend cycle, B iterationpreliminary trend cycle, C iterationpreliminary trend cycle, D iterationmodified seasonally adjusted seriesunmodified SI ratios, B iterationmodified irregular seriesreplacement values for extremes of SI componentmodified SI ratios, C iterationmodified SI ratios, D iterationpreliminary seasonal factors, B iterationpreliminary seasonal factors, C iterationpreliminary seasonal factors, D iteration% in the original series% in the original series (saved as percentages if appropriate)preliminary seasonally adjusted series, B iterationpreliminary seasonally adjusted series, C iterationpreliminary seasonally adjusted series, D iteration% in seasonally adjusted series (D11)% in seasonally adjusted series (D11 - saved as percentages if appropriate)preliminary trend cycle, B iterationpreliminary trend cycle, C iterationpreliminary trend cycle, D iteration% in final trend cycle (D12)% in final trend cycle (D12 - saved as percentages if appropriate )!unmodified SI ratios, B iterationfinal unmodified SI ratiosfinal unmodified SI ratios, with labels for outliers and extreme values% in original series adjusted for calendar factors (A18)% in original series adjusted for calendar factors (A18 - saved as percentages if appropriate)replacement values for extremes of SI componentmodified SI ratiosfinal replacement values for SI ratiosseasonal factors, B iterationseasonal factors, C iterationfinal seasonal factorsfinal seasonal factors (saved as percentages if multiplicative adj)final seasonal differenceseasonal factors, adjusted for user-defined seasonal regARIMA componentseasonal factors, before shrinkage appliedseasonally adjusted data, B iterationseasonally adjusted data, C iterationfinal seasonally adjusted datafinal seasonally adjusted series with constant value addedseasonally adjusted series with alternative extreme value modificationfinal trend cyclefinal trend cycle, adjusted for level change outliersbias correction factorsfinal trend cycle with constant value addedirregular component, B iterationirregular component, C iterationfinal irregular componentfinal irregular component (saved as percentages if multiplicative adj)final irregular component, adjusted for additive outlierspreliminary weights for irregular componentfinal weights for irregular componentpreliminary extreme value adjustment factorsfinal extreme value adjustment factors&X-11 Easter adjustment factorscombined holiday componentcombined adjustment factorscombined adjustment factors (saved as percentages if multiplicative adj)final adjustment differencescombined calendar adjustment factorsfinal adjustment ratiostotal adjustment factorsoriginal series adjusted by preliminary irregular regression factorsoriginal series adjusted by final irregular regression factorssummary measuresmonitoring and quality assessment statistics^ of annual totalsF-tests for seasonalityMoving seasonality ratiofinal seasonal filter selection via GLOBAL MSRoriginal series,@-seasonally adjusted series,coincidence of points^ of the original series modified for extremes^ of the S. A. series modified for extremesfinal seasonal factors with one year forecastsfinal seasonally adjusted seriesfinal trend cyclefinal irregular componentforecasts of final seasonally adjusted seriesforecasts of final trend cycleforecasts of final irregular weightsfinal seasonally adjusted series with forced yearly totalsrounded final seasonally adjusted series% in seasonally adjusted series with forced yearly totals (D11.A)% in seasonally adjusted series with forced yearly totals (D11.A - saved as percentages if appropriate)% in rounded seasonally adjusted series (D11.R)% in rounded seasonally adjusted series (D11.R - saved as percentages if appropriate)factors applied to adjusted series to get adjusted series with forced yearly totalsratios or differences in annual totals and indirect seasonally adjusted seriesfactors applied to get adjusted series with forced yearly totalsprior trading day factorsextreme irregular values excluded from irregular component regressionextreme irregular values excluded from irregular component regressionpreliminary irregular component regressionfinal irregular component regressionpreliminary trading day factors from irregular component regressionfinal trading day factors from irregular component regressionpreliminary combined trading day factors from irregular component regressionfinal combined trading day factors from irregular component regressionpreliminary holiday factors from irregular component regressionfinal holiday factors from irregular component regressionpreliminary calendar factors from irregular component regressionfinal calendar factors from irregular component regressionpreliminary combined calendar factors from irregular component regressionfinal combined calendar factors from irregular component regressionAO outlier detection results for irregular component regression, by iterationregression matrix used in final irregular component regressioncovariance matrix of irregular component regression parameter estimatesresults of AIC tests used in final irregular component regression1revisions history analysisrevision history of the outliers identifiedrevision history of the Moving Seasonality Ratiopercent revisions of the concurrent seasonal adjustmentssummary statistics : average absolute percent revisions of the seasonal adjustmentsconcurrent and revised seasonal adjustments and revisionspercent revisions of the % of the adjustmentssummary statistics : average absolute revisions of the % of the adjustmentshistory of the % of the adjustmentspercent revisions of the concurrent indirect seasonal adjustmentssummary statistics : average absolute percent revisions of the concurrent indirect seasonal adjustmentsconcurrent and revised indirect seasonal adjustments and revisionspercent revision of the concurrent Henderson trend-cycle valuessummary statistics : average absolute percent revision of the concurrent Henderson trend-cycleconcurrent and revised Henderson trend-cycle values and revisionspercent revisions of the % of the trend-cycle valuessummary statistics : average absolute percent revisions of the % of the trend-cyclehistory of the % of the trend-cycle valuesrevisions of the concurrent and projected seasonal componentsummary statistics : average absolute percent revisions of the concurrent and projected seasonal componentconcurrent and projected seasonal component and their percent revisionsrevision history of the likelihood statisticsrevision history of the out-of-sample forecastsforecast and forecast error historySEATS ARIMA model historyseasonal forecast historyARMA model coefficient historytrading day coefficient historysliding spans of the seasonal factorssliding spans of the indirect seasonal factorssliding spans of the changes in the seasonally adjusted seriessliding spans of the changes in the indirect seasonally adjusted seriessliding spans of the seasonally adjusted seriessliding spans of the indirect seasonally adjusted seriessliding spans of the year-to-year changes in the seasonally adjusted seriessliding spans of the year-to-year changes in the indirect seasonally adjusted seriessliding spans of the trading day factors#composite time series data (for the span analyzed)prior adjusted composite datacomposite series (prior adjusted)composite series (prior adjusted)regARIMA calendar adjusted composite dataregARIMA outlier adjusted composite dataindirect seasonal adjustment of composite seriescomposite smoothness diagnosticsindirect unmodified SI componentfinal replacement values for SI component of indirect adjustmentindirect seasonal componentindirect seasonal component (saved as percentages if multiplicative adj)indirect final seasonal differenceindirect seasonally adjusted dataindirect trend cycleindirect irregular componentindirect irregular component (saved as percentages if multiplicative adj)original data modified for extremes from indirect adjustmentseasonally adjusted data modified for extremes from indirect adjustmentirregular component modified for extremes from indirect adjustment%s for composite series%s for composite series (saved as percentages if appropriate)%s for indirect seasonally adjusted series%s for indirect seasonally adjusted series (saved as percentages if appropriate)%s for indirect seasonally adjusted series with forced yearly totals%s for indirect seasonally adjusted series with forced yearly totals (saved as percentages if appropriate)%s for rounded indirect seasonally adjusted series%s for rounded indirect seasonally adjusted series (saved as percentages if appropriate)%s for indirect trend component%s for indirect trend component (saved as percentages if appropriate)% in original series adjusted for calendar effects% in original series adjusted for calendar effects (saved as percentages if appropriate)robust estimate of the indirect final seasonally adjusted seriesindirect final adjustment ratiosindirect total adjustment factors>MCD moving average for indirect adjustmentsummary measures (indirect)monitoring and quality assessment statistics (indirect)ratios of annual totals for indirect adjustmentF-tests for seasonalitymoving seasonality ratiofinal indirect seasonally adjusted series with forced yearly totalsrounded indirect final seasonally adjusted seriescomposite seriesoriginal series,@-indirect seasonally adjusted series,coincidence of points^ of the composite series modified for extremes^ of the S. A. series modified for extremesfinal indirect seasonal factors with one year forecastsfinal indirect seasonally adjusted seriesfinal trend cycle from the indirect seasonal adjustmentfinal indirect irregular componentindirect level change adjustment factorsindirect additive outlier adjustment factorsindirect calendar componentindirect combined adjustment factorsindirect combined adjustment factors (saved as percentages if multiplicative adj)factors applied to adjusted series to get adjusted series with forced yearly totalsratios or differences in annual totals and indirect seasonally adjusted seriesfactors applied to get indirect adjusted series with forced yearly totalsW/final trend component (SEATS)final trend cycle with constant value added (SEATS)final seasonal component (SEATS)final seasonal component (SEATS, saved as a percent if log transformation used)final irregular component (SEATS)final irregular component (SEATS, saved as a percent if log transformation used)final seasonally adjusted series (SEATS)final seasonally adjusted series with constant value added (SEATS)final transitory component (SEATS)final transitory component (SEATS, saved as a percent if log transformation used)final combined adjustment factors (SEATS)final combined adjustment factors (SEATS, saved as a percent if log transformation used)final trend component forecast decomposition (SEATS)final seasonal component forecast decomposition (SEATS)series forecast decomposition (SEATS)final seasonally adjusted series forecast decomposition (SEATS)final transitory component forecast decomposition (SEATS)final adjustment ratios (SEATS)total adjustment factors (SEATS)Wiener-Kolmogorov end filtercomponent modelspseudo innovations in trend-cyclepseudo innovations in seasonalpseudo innovations in transitory componentpseudo innovations in seasonally adjusted seriessquared gain of the symmetric seasonal adjustment filtersquared gain of the concurrent seasonal adjustment filtersquared gain of the symmetric trend filtersquared gain of the concurrent trend filtertime shift of the concurrent seasonal adjustment filtertime shift of the concurrent trend filtersymmetric seasonal adjustment filterconcurrent seasonal adjustment filtersymmetric trend filterconcurrent trend filterdifferenced original series after transformation, prior adjustment (SEATS)differenced final seasonally adjusted series (SEATS)differenced final trend (SEATS)sum of final seasonal component (SEATS)final cyclefinal long term trendstandard error of final seasonal component (SEATS)standard error of final seasonally adjusted series (SEATS)standard error of final trend component (SEATS)standard error of final transitory component (SEATS)final seasonally adjusted series adjusted for outliers (SEATS)final irregular component outlier adjusted (SEATS)getdiag.f( ' *** No differencing provided, finite sample', ' diagnostic processing aborted. ***' )$@ H ?Y@h㈵>Expected specification name but found "" is not a valid spec name. Expected "{" but found also found on line position of the input file. typeroundtargetstartlambdarhomodeprintsaveindforceusefcstnonedentonregress(Entry for type argument must be none, denton or regress.yesnoAvailable options for round are yes or no.originalcalendaradjpermprioradjbothEntry for forcetarget argument must be original, calendaradj, permprioradj, or both.janfebmaraprmayjunjulaugsepoctnovdecjanuaryfebruarymarchaprilmayjunejulyaugustseptemberoctobernovemberdecemberq1q2q3q4Choices for start are the name of a month or quarter.No seasonal period specified in series spec.This entry for start only valid for monthly data.This entry for start only valid for quarterly data.Available options for indforce are yes or no.Available options for usefcst are yes or no.Value of lambda must be between -3 and 3.Value of rho must be greater than 0 and less than or equal to 1.ratiodiffAvailable options for model are ratio or diff. 8!P!P!Ph"P#P 'P%P]&P#$P:$PQ$P%P(@ diffsdiffmaxlagprintsave(Must specify a seasonal period, PERIOD>1, to use SDIFF.Need to remove fixed seasonal effects in order to identify seasonal orders of differencing#Expected an integer or an integer list, not ""Found a NULL value; check your commas.Integer vector exceeds , the maximum number of elements.Expected an integer not "Found a NULL value; check for null list.Expected ")" after (AR DIFF MAPeriod specified in (AR DIFF MA)period must be greater than zero.Must explicitly specify the period in (AR DIFF MA)periodToo many operators in specified ARIMA model$Order of the AR operator is too large.Order of the AR operator cannot be less than zero.Cannot have a seasonal difference with seasonal regression effects.Order of the differencing operator is too large.Order of the full differencing operator is too large.Order of the differencing operator cannot be less than zero.Order of the MA operator is too largeOrder of the MA operator is too large.Order of the MA operator cannot be less than zero.Expected "(" in (AR DIFF MA)8Expected an INTEGER or "[" not ""Found a NULL lag; check your commas.Expected an integer not "DIFFARMA vector exceeds $ lag[s].Lags specified in model must be positive integers.No room to add more ARIMA coefficients. Reduce the model order.Lags must be specified from smallest to largest; lags will be sorted.]Maximum number of lags, , exceeded.Maximum number of ARIMA coefficients, , exceeded. Reduce the model order.8defaultnonebriefalltablesallPrefix must be "+", "-", or nothing.headerhdrspana1seriesplota1pspecfilespcsavefilesavseriesmvadjmvcalendaradjoriga18outlieradjoriga19adjoriginalb1adjorigplotb1pseriesconstanta1cseriesconstantplotacppriora2permpriora2ptemppriora2tprioradjusteda3permprioradjusteda3pprioradjustedptda4dpermprioradjustedptda4ptransformedtrnaictransformtacregressionmatrixrmxaictestatsoutlierotlaoutlieraolevelshiftlstemporarychangetcseasonaloutliersotradingdaytdholidayholuserdefusrregseasonala10transitorya13chi2testctsdailyweightstdwacfiacacfplotacppacfipcpacfplotpcpregcoefficientsrgcheaderhdrunitroottesturtautochoiceachunitroottestmdlurmautochoicemdlamdbestfivemdlb5mautooutlierhdraohautooutlieritraoiautooutliertestsaotautofinaloutliertestsaftautodefaulttestsadtautoljungboxtestalbautofinaltestsaftheaderhdrheaderbcsthdbusermodelsumdpickmdlchoicepchoptionsoptiterationsitriterationerrorsitemodelmdlregcmatrixrcmestimatesestarmacmatrixacmlkstatslkslformulaslkfrootsrtsregressioneffectsrefresidualsrsdregressionresidualsrrsaveragefcsterrafcheaderhdriterationsoittestsotstemporarylstlsfinaltestsftsacfacfacfplotacppacfpcfpacfplotpcpacfsquaredac2acfsquaredplotap2histogramhstnormalitytestnrmdurbinwatsondwfriedmantestfrttransformedftrvariancesfvrforecastsfcttransformedbcstbtrbackcastsbctspecorigsp0specresidualsprspecsasp1specirrsp2specseatssas1sspecseatsirrs2sspecextresidualsserspecindsais1specindirris2speccompositeis0spectukeyorigst0spectukeyresidualstrspectukeysast1spectukeyirrst2spectukeyseatssat1sspectukeyseatsirrt2sspectukeyextresidualsterspectukeyindsait1spectukeyindirrit2spectukeycompositeit0qsqstukeypeakstpkadjoriginalcc1adjoriginaldd1modoriginale1mcdmovavgf1trendb2b2trendc2c2trendd2d2modseasadje2sib3b3modirregulare3replacsib4b4modsic4c4modsid4d4seasonalb5b5seasonalc5c5seasonald5d5origchangese5origchangespctpe5seasadjb6b6seasadjc6c6seasadjd6d6sachangese6sachangespctpe6trendb7b7trendc7c7trendd7d7trendchangese7trendchangespctpe7sib8b8unmodsid8unmodsioxd8bcalendaradjchangese8calendaradjchangespctpe8replacsib9b9replacsic9c9replacsid9seasonalb10b10seasonalc10c10seasonald10seasonalpctpsfseasonaldifffsdseasonaladjregseaarsseasonalnoshrinksnsseasadjb11b11seasadjc11c11seasadjd11seasadjconstsacrobustsae11trendd12trendadjlstalbiasfactorbcftrendconsttacirregularbb13irregularcc13irregulard13irregularpctpirirregularadjaoirairrwtbb17irrwtc17extremebb20extremec20x11easterh1combholidaychladjustfacd16adjustfacpctpafadjustdifffadcalendard18adjustmentratioe18totaladjustmenttadtdadjorigbb19tdadjorigc19ftestb1b1fx11diagf2qstatf3yrtotalse4ftestd8d8fmovseasratd9aresidualseasfrsfautosfasftdaytypetdyorigwsaplote0ratioplotorigra1ratioplotsara2seasonalplotsfpseasadjplotsaptrendplottrpirregularplotirpseasadjfcstsaftrendfcsttrfirrwtfcstiwfseasadjtotsaasaroundrndrevsachangese6arevsachangespctp6arndsachangese6rrndsachangespctp6rcratiocrrratiorrforcefactorffcpriortda4extremevalbb14extremevalc14x11regbb15x11regc15tradingdaybb16tradingdayc16combtradingdaybb18combtradingdayc18holidaybbxhholidayxhlcalendarbbxccalendarxcacombcalendarbbcccombcalendarxccoutlierhdrxohoutlieriterxoioutliertestsxotoutlierfinaltestsxftxregressionmatrixxrmxregressioncmatrixxrcxaictestxatheaderhdroutlierhistoryrotsfilterhistorysfhsarevisionssarsasummarysassaestimatessaechngrevisionschrchngsummarychschngestimatescheindsarevisionsiarindsasummaryiasindsaestimatesiaetrendrevisionstrrtrendsummarytrstrendestimatestretrendchngrevisionstcrtrendchngsummarytcstrendchngestimatestcesfrevisionssfrsfsummarysfssfestimatessfelkhdhistorylkhfcsterrorsfcefcsthistoryfchseatsmdlhistorysmhseasonalfcthistoryssharmahistoryamhtdhistorytdhheaderhdrssftestssffactormeansfmnindfactormeansfmipercentpctindpercentpciyypercentpcyindyypercentpiysummarysumindsummarysmiyysummarysuyindyysummarysiysfspanssfsindsfspanssischngspanschsindchngspanscissaspansadsindsaspansaisychngspansycsindychngspansyistdspanstdscompositesrscmsprioradjcompositeia3adjcompositesrsb1adjcompositeplotb1pcalendaradjcompositecacoutlieradjcompositeoacheaderhdrindtestittindunmodsiid8indreplacsiid9indseasonalisfindseasonalpctipsindseasonaldiffisdindseasadjisaindtrenditnindirregulariirindirregularpctipiindmodoriginalie1indmodsadjie2indmodirrie3origchangesie5origchangespctip5indsachangesie6indsachangespctip6indrevsachangesi6aindrevsachangespctipaindrndsachangesi6rindrndsachangespctiprindtrendchangesie7indtrendchangespctip7indcalendaradjchangesie8indcalendaradjchangespctip8indrobustsaieeindadjustmentratioi18indtotaladjustmentitaindmcdmovavgif1indx11diagif2indqstatif3indyrtotalsie4indftestd8idfindmovseasratimsindresidualseasfirfindadjsatotiaaindsadjroundirncompositeplotcmporigwindsaplotie0ratioplotorigir1ratioplotindsair2indseasonalplotispindseasadjplotiapindtrendplotitpindirregularplotiipindlevelshiftilsindaoutlieriaoindcalendaricaindadjustfaciafindadjustfacpctipfindcratiocriindrratiorriindforcefactorifftrends12trendconststcseasonals10seasonalpctpssirregulars13irregularpctpsiseasonaladjs11seasadjconstsectransitorys14transitorypctpscadjustfacs16adjustfacpctpsatrendfcstdecomptfdseasonalfcstdecompsfdseriesfcstdecompofdseasonaladjfcstdecompafdtransitoryfcstdecompyfdadjustmentratios18totaladjustmentstawkendfilterwkfcomponentmodelsmdcpseudoinnovtrendpicpseudoinnovseasonalpispsuedoinnovtransitorypitpsuedoinnovsadjpiasquaredgainsasymgafsquaredgainsaconcgacsquaredgaintrendsymgtfsquaredgaintrendconcgtctimeshiftsaconctactimeshifttrendconcttcfiltersasymfaffiltersaconcfacfiltertrendsymftffiltertrendconcftcdifforiginaldordiffseasonaladjdsadifftrenddtrseasonalsumssmcyclecyclongtermtrendlttseasonalsesseseasonaladjseasetrendsetsetransitorysecseseasonaladjoutlieradjse2irregularoutieradjse3Print or level argument is not defined. Check the available table names and levels for this spec.Unexpected EOFFound a NULL value; check your commas.Prefix must be "+", "-", or nothingP* variablesuserdatastartfileformatbprintsaveaictesteastermeansnoapplyusertypetcrateaicdiffsavelogcenteruserchi2testchi2testcvtlimitpvaictest4(Getting data from a fileAlready have user regression tdtdnolpyeartdstocktd1coeftd1nolpyeartdstock1coefeastereasterstockuserlomloqlpyearChoices for aictest are td, tdnolpyear, tdstock, td1coef, td1nolpyear, tdstock, tdstock1coef, lom, loq, lpyear, easter, easterstock, and user.Can only specify one of easter and easterstock in aictest.Can only specify one of lom, loq, or lpyear in aictest.Can only specify one type of trading day in aictest.yesnoChoices for eastermeans are yes and no.tdaolsholidayuserseasonalusertcsoChoices for the noapply argument are td, ao, ls, holiday, or user.constantseasonaltdtdstocklomloqlpyearlomstockeastersceasterlaborthanksholidayholiday2holiday3holiday4holiday5aolsrptcsotransitoryeasterstockuserImproper entry for usertype. See Section 7 of Reference Manual.meanseasonalChoices for centeruser are mean and seasonal.Cannot specify tcrate in both the regression and outlier specsValue of tcrate must be between 0 and 1.8Choices for chi2test are yes and no.Value of chi2testcv must be between 0 and 1.Value of tlimit must be greater than 0.Value of pvaictest must be greater than 0.Value of pvaictest must be less than 1.?Leap Year(' ERROR: Number of initial values is not the same as ', 'the number of regression',/,' variables.')(/,' ERROR: Need to specify both user-defined ', 'regression variables (with user',/, ' argument) and X matrix (with file or data ', 'argument).')(' ERROR: Cannot specify holiday group types for ', 'user-defined regression',/, ' variables out of sequence.')(/,' ERROR: Number of user-defined X elements=',i4, /,' not equal to a multiple of the number of ', 'columns=',i3,'.',/)span of the datauser-defined regression variables1User-defined Holiday2User-defined Holiday Group 23User-defined Holiday Group 3User-defined Holiday Group 45User-defined Holiday Group 5&User-defined SeasonalUser-defined(' ERROR: Cannot specify group types for ', 'user-defined regression',/, ' variables if user-defined regression ', 'variables are not',/, ' defined in the regression spec.')WARNING: The program will only perform an AIC test on the length of month regressor for monthly time series.WARNING: The program will only perform an AIC test on the length of quarter regressor for quarterly time series.WARNING: The program will only perform an AIC test on the leap year regressor for monthly or quarterly time series.ERROR: AIC test for the length of month regressor cannot be specified whenERROR: AIC test for the length of quarter regressor cannot be specified when the td or td1coef option is given in the variables argument.ERROR: AIC test for the leap year regressor cannot be specified when the td or td1coef option is given in the variables argument and a power transformation is performed.PPPPPPmPP)P@PWP`PPPCP-PPP PPhP Pgetreg.fWARNING: Revisions history analysis of the percent changes of the seasonally adjusted series has ceased due to negative values in the seasonally adjusted series. trend has ceased due to negative values in the trend.spana1specfilespcseriesmvadjmvcalendaradjoriga18outlieradjoriga19adjoriginalb1seriesconstanta1cpriora2permpriora2ptemppriora2tprioradjusteda3permprioradjusteda3pprioradjustedptda4dpermprioradjustedptda4ptransformedtrnregressionmatrixrmxoutlierotlaoutlieraolevelshiftlstemporarychangetcseasonaloutliersotradingdaytdholidayholuserdefusrregseasonala10transitorya13acfiacpacfipciterationsitrmodelmdlregcmatrixrcmestimatesestarmacmatrixacmlkstatslksrootsrtsregressioneffectsrefresidualsrsdregressionresidualsrrsiterationsoitfinaltestsftsacfacfpacfpcfacfsquaredac2transformedftrvariancesfvrforecastsfcttransformedbcstbtrbackcastsbctspecorigsp0specresidualsprspecsasp1specirrsp2specseatssas1sspecseatsirrs2sspecextresidualsserspecindsais1specindirris2speccompositeis0spectukeyorigst0spectukeyresidualstrspectukeysast1spectukeyirrst2spectukeyseatssat1sspectukeyseatsirrt2sspectukeyextresidualsterspectukeyindsait1spectukeyindirrit2spectukeycompositeit0adjoriginalcc1adjoriginaldd1modoriginale1mcdmovavgf1trendb2b2trendc2c2trendd2d2modseasadje2sib3b3modirregulare3modsic4c4modsid4d4seasonalb5b5seasonalc5c5seasonald5d5origchangese5origchangespctpe5seasadjb6b6seasadjc6c6seasadjd6d6sachangese6sachangespctpe6trendb7b7trendc7c7trendd7d7trendchangese7trendchangespctpe7sib8b8unmodsid8unmodsioxd8bcalendaradjchangese8calendaradjchangespctpe8replacsic9c9replacsid9seasonalb10b10seasonalc10c10seasonald10seasonalpctpsfseasonaldifffsdseasonaladjregseaarsseasonalnoshrinksnsseasadjb11b11seasadjc11c11seasadjd11seasadjconstsacrobustsae11trendd12trendadjlstalbiasfactorbcftrendconsttacirregularbb13irregularcc13irregulard13irregularpctpirirregularadjaoirairrwtbb17irrwtc17extremebb20extremec20x11easterh1combholidaychladjustfacd16adjustfacpctpafadjustdifffadcalendard18adjustmentratioe18totaladjustmenttadtdadjorigbb19tdadjorigc19yrtotalse4seasadjfcstsaftrendfcsttrfirrwtfcstiwfseasadjtotsaasaroundrndrevsachangese6arevsachangespctp6arndsachangese6rrndsachangespctp6rcratiocrrratiorrforcefactorffcpriortda4extremevalbb14extremevalc14x11regbb15x11regc15tradingdaybb16tradingdayc16combtradingdaybb18combtradingdayc18holidaybbxhholidayxhlcalendarbbxccalendarxcacombcalendarbbcccombcalendarxccoutlieriterxoixregressionmatrixxrmxregressioncmatrixxrcoutlierhistoryrotsfilterhistorysfhsarevisionssarsaestimatessaechngrevisionschrchngestimatescheindsarevisionsiarindsaestimatesiaetrendrevisionstrrtrendestimatestretrendchngrevisionstcrtrendchngestimatestcesfrevisionssfrsfestimatessfelkhdhistorylkhfcsterrorsfcefcsthistoryfchseatsmdlhistorysmhseasonalfcthistoryssharmahistoryamhtdhistorytdhsfspanssfsindsfspanssischngspanschsindchngspanscissaspansadsindsaspansaisychngspansycsindychngspansyistdspanstdscompositesrscmsprioradjcompositeia3adjcompositesrsb1calendaradjcompositecacoutlieradjcompositeoacindunmodsiid8indreplacsiid9indseasonalisfindseasonalpctipsindseasonaldiffisdindseasadjisaindtrenditnindirregulariirindirregularpctipiindmodoriginalie1indmodsadjie2indmodirrie3origchangesie5origchangespctip5indsachangesie6indsachangespctip6indrevsachangesi6aindrevsachangespctipaindrndsachangesi6rindrndsachangespctiprindtrendchangesie7indtrendchangespctip7indcalendaradjchangesie8indcalendaradjchangespctip8indrobustsaieeindadjustmentratioi18indtotaladjustmentitaindmcdmovavgif1indyrtotalsie4indadjsatotiaaindsadjroundirnindlevelshiftilsindaoutlieriaoindcalendaricaindadjustfaciafindadjustfacpctipfindcratiocriindrratiorriindforcefactorifftrends12trendconststcseasonals10seasonalpctpssirregulars13irregularpctpsiseasonaladjs11seasadjconstsectransitorys14transitorypctpscadjustfacs16adjustfacpctpsatrendfcstdecomptfdseasonalfcstdecompsfdseriesfcstdecompofdseasonaladjfcstdecompafdtransitoryfcstdecompyfdadjustmentratios18totaladjustmentstawkendfilterwkfcomponentmodelsmdcpseudoinnovtrendpicpseudoinnovseasonalpispsuedoinnovtransitorypitpsuedoinnovsadjpiasquaredgainsasymgafsquaredgainsaconcgacsquaredgaintrendsymgtfsquaredgaintrendconcgtctimeshiftsaconctactimeshifttrendconcttcfiltersasymfaffiltersaconcfacfiltertrendsymftffiltertrendconcftcdifforiginaldordiffseasonaladjdsadifftrenddtrseasonalsumssmcyclecyclongtermtrendlttseasonalsesseseasonaladjseasetrendsetsetransitorysecseseasonaladjoutlieradjse2irregularoutieradjse3Save argument is not defined. Check the available table names for this spec.Unexpected EOFFound a NULL value; check your commas.Seasonal MA0 datastartperiodspantitlefileformatprintsavenameprecisiondecimalsmodelspancomptypecompwtmissingcodemissingvalsaveprecisionyr2000trimzerodivpowerappendfcstappendbcsttypeCannot use data argument when a data metafile is used.Use either data or file, not both(Invalid seasonal periodSeasonal period too large. See Section 2.7 of the Reference Manual on program limitsAssumed seasonal period of 12Need two dates for the span or use a comma as place holder.Cannot use file argument when a data metafile is used. @Number of input decimals must be between 0 and 5, inclusiveNumber of output decimals must be between 0 and 5, inclusiveNeed two dates for the model span or use a comma as place holder.noneaddsubmultdivAvailable composite types are none, add, sub, mult, div.Value of composite weight must be greater than zero.yesnoAvailable options for yr2000 are yes or no.yesspannoAvailable options for trimzero are yes, span or no.Value entered for divpower must be between -9 and 9, inclusive.Available options for appending forecasts are yes or no.Available options for appending backcasts are yes or no.flowstockAvailable options for type are flow or stock.Start date not validSpan starting date not validSpan ending date not validMust specify starting and ending span when trimzero=span.No time series specifiedTime series could not be read due to previously found errorsSpan not within the seriesspanseriesModel span starting date not validModel span ending date not validModel span not within the span of available data.model spanPPP/PoPPPPPPP`PPP&PPPPGPPmPPP]PP startcutseascutchngcuttdoutlierfixmdlprintsavelengthtransparentsavelogfixregadditivesanumspansx11outlierfixx11reg(Value of cutseas must be greater than zero.Value of cutchng must be greater than zero.Value of cuttd must be greater than zero.removekeepyesAvailable options for outlier are no, keep, or yes.noyesclearAvailable options for fixmdl are no, clear, or yes.Length of sliding spans must be greater than or equal to 3 years.Length of sliding spans must be less than or equal to years.yesnoAvailable options for x11outlier are no or yes.Available options for transparent are no or yes.8tdholidayuseroutlierAvailable options for fixreg are td, holiday, or user.differencepercentAvailable options for additivesa are difference or percent.Value of spans must be greater than one.Value of spans must be less than or equal to .Available options for fixx11reg are no or yes.LPLPPRP PPXPPP.PxP'P>PPfPPPIndex out of range vectorCharacter string too long for target.autotransformatrautomodelamdautodiffadfbestfivemdlb5mmeanmufinalunitrootfuralldiagnosticsallautomodelamdaicaicaiccaccbicbichannanquinnhqeiceicaveragefcsterrafcalldiagnosticsallaictestatschi2testctsidentifiedidnormalitytestnrmljungboxqlbqboxpierceqbpqseasftestsfttdftesttftdurbinwatsondwfriedmantestfrtalldiagnosticsallm1m1m2m2m3m3m4m4m5m5m6m6m7m7m8m8m9m9m10m10m11m11qqq2q2movingseasratiomsricratioicrfstableb1fb1fstabled8fd8movingseasfmsfidseasonalidsalldiagnosticsallaictestatsaveabsrevsaasaaveabsrevchngachaveabsrevindsaiaaaveabsrevtrendatraveabsrevtrendchngatcaveabsrevsfasfaveabsrevsfprojaspavesumsqfcsterrafealldiagnosticsallpercentpctpercentspcspeaksspkdirpeaksdpkindpeaksipktukeypeakstpkdirtukeypeaksdtpindtukeypeaksitpqsqsdirqsdqsindqsiqsalldiagnosticsallindm1im1indm2im2indm3im3indm4im4indm5im5indm6im6indm7im7indm8im8indm9im9indm10imtindm11imeindqiqindq2iq2indmovingseasratioisrindicratioiirindfstabled8id8indmovingseasfisfindidseasonaliidindtestittalldiagnosticsallseatsmodelsmdx12modelxmdnormalitytestnrmtotalsquarederrortsecomponentvariancecvrconcurrentesterrorceepercentreductionseprsaverageabsdiffannualaadoverunderestimationoueoverunderstatisticsousseasonalsignifssgdurbinwatsondwsfriedmanfrsalldiagnosticsallSavelog argument is not defined. Check the available diagnostics for this spec.Unexpected EOFFound a NULL value; check your commas.Expected a NAME, QUOTE, or list of either, not an empty string.This title will be truncated at the first characters.Expected a NAME or a QUOTE or a list of either, not ""Found a NULL value; check your commas.List of names exceeds , the maximum number of elements.?Expected a NAME or QUOTE not "8 2modesigmalimseasonalmatrendmatitleextremeadjtypeappendfcsttrendiccalendarsigmasigmavecx11eastertaperkeepholidayfinalsfshortprintsavesavelogprint1stpassexcludefcsttrue7termshrinkcenterseasonalappendbcstmultaddlogaddpseudoadd(Improper seasonal adjustment mode: valid choices for mode are mult, add, logadd or pseudoadd.Two sigma limits needed (or use a comma as place holder).Sigma limits must be greater than zero.Lower sigma limit must be less than upper sigma limit.x11defaults3x3s3x5s3x9s3x15stablemsrs3x1Improper value(s) entered for seasonalma. Valid choices of seasonal filter are s3x1, s3x3, s3x5, s3x9, s3x15, stable, msr, or x11default.No seasonal period specified in series spec.Specify either 1 or seasonal filters (or use a comma as a place holder).Length of Henderson trend filter must be a positive odd integer.  stdwmadwmadlogtautaulogImproper X-11 outlier option: valid choices for extremeadj are std, wmad, wmadlog, tau, taulog.sasummarytrendThe available adjustment types are sa, summary, or trend.yesnoAvailable options for appending forecasts are yes or no.Available options for print1stpass are yes or no.Specified I/C ratio must be greater than zero.nonesignifallselectAvailable options for calendarsigma are none, signif, all or select.janfebmaraprmayjunjulaugsepoctnovdecjanuaryfebruarymarchaprilmayjunejulyaugustseptemberoctobernovemberdecemberq1q2q3q4Improper value(s) entered for sigmavec. Valid choices for sigmavec are the name(s) of a month or quarter.Entry for sigmavec not valid for monthly data.Entry for sigmavec not valid for quarterly data.Available options for centerseasonal are yes or no.Available options for appending backcasts are yes or no.nonegloballocalEntry for shrink argument must be none, global or local.Available options for x11easter are yes or no.Value of taper must be between zero and 1.Available options for keepholiday are yes or no.aolsusertcChoices for final argument are ao, ls, tc, or user.Available options for sfshort are yes or no.ZqAvailable options for excludefcst are yes or no.Available options for true7term are yes or no.4Q4Q!QQQTQQYQ Q[ Q Q QcQQQmQQ4QKQbQ QyQ(QQ^ Q Q -M-mgetxop.f(/,a) ERROR: Cannot specify data (-d) and input (-m) metafiles in the same run. ERROR: An input metafile name must immediately follow the -m flag.-D-d ERROR: A data metafile name must immediately follow the -d flag.-I-i ERROR: An input spec file name must immediately follow the -i flag.-O-o ERROR: An output file name must immediately follow the -o flag.-G-g ERROR: A graphics file directory name must immediately follow the -g flag.-V-v-C-c-S-s-N-n-W-w-P-p-R-r-Q-q- ERROR: No program option specified after the dash (-).(/,' ERROR: Program option ',a,' not defined. ', 'Valid program options are ',/,' -I, -O, -M, ', '-D, -C, -P, -W, -S, -N, -V, -R, -Q.')(/,' ERROR: Program option ',a,' not defined; valid ', 'options must be preceded',/,' by a dash (-): ', '-I, -O, -M, -D, -C, -P, -W, -S, -N, -V, -R, -Q, -A.')(/,' ERROR: Must specify metafile input (-m metafile)', ' when using composite',/,' option (-c).')(/,' ERROR: Cannot specify data metafile input (-d ', 'datametafile) when using',/, ' composite option (-c).')(/,' NOTE: Input verification option (-v) is specified ', 'in the same run as',/, ' the composite (-c), diagnostic storage (-s),', ' no print (-n),',/, ' wide printout (-w), or page suppress (-p) ', 'options. These',/, ' other flags have been ignored.')(/,' ERROR: Cannot specify metafile input (-m metafile)', ' when using an ',/,' alternate output file ', 'name (-o outfile).')(/,' ERROR: Cannot specify metafile input (-m metafile)', ' and single file input',/,' (-i infile or ', 'infile) in the same run.')(/,' ERROR: Must specify either an input specification ', 'file name', /,' (-i infile or infile) or an input metafile ', 'name (-m metafile).',/, /,' See ',a,' of the ',a,' ',a,' for more', /,' information on how to run ',a,'.')Section 2X-13ARIMA-SEATSReference ManualTrading DayStock Trading Day8U?Y@dAExpected argument name or "}" but found ""Argument name "" not found Expected "=" but found "" also found on line position of the input file. titlemodeldiffarma(@Q@Qm@Q AQ AQ AQ.maxdiffub1ub2cancelmaxorderdiffprintsavelogbalancedexactdiffhrinitialarmalimitpercentrsereducecvljungboxlimitacceptdefaultnoautooutlierurfinalfirstarcheckmumixedrejectfcstfcstlim((' NOTE: Arguments diff and maxdiff are both specified;', /,' only maxdiff will be used.')Two values are needed.Maximum order of regular differencing must be less than or equal to 2.Maximum order of seasonal differencing must be less than or equal to 1.Maximum order of differencing specified must be greater than zero.Initial unit root limit must be greater than one.Final unit root limit must be greater than zero.Final unit root limit must be less than one.Cancelation limit must be greater than zero.Value of firstar must be 2, 3 or 4.Two values are needed (or use a comma as place holder).AR and MA orders must be greater than or equal to zero.Regular orders must be less than or equal to 4.Seasonal orders must be less than or equal to 2.Order of regular differencing must be less than or equal to 2.Order of seasonal differencing must be less than or equal to 1.Order of differencing specified must be greater than zero. yesnoAvailable options for balanced are yes or no.noyesfirstAvailable options for exactdiff are yes, first or no.Available options for hrinitial are yes or no.Final limit for ARMA t-value must be greater than zero.Percentrse must be greater than zero.Percent reduction in critical value must be greater than zero.Percent reduction in critical value cannot be greater than 1.Ljung-Box Q probability limit cannot be less than zero.Ljung-Box Q probability limit must be less than one.Available options for acceptdefault are yes or no.sametramoAvailable options for noautooutlier are same or tramo.Unit root limit for final model must be greater than one.Available options for checkmu are yes or no.Available options for mixed are yes or no.Available options for rejectfcst are yes or no.Forecast error limit cannot be less than zero.Forecast error limit cannot be greater than 100.2/9BQ9BQ#DQDQEQFQ0HQJQ.JQEJQJQKQNLQLQMQiNQQQQQRQKSQgtauto.f modefileqlimfcstlimbcstlimoverdiffprintmethodoutofsampleidentifysavelogbothfcst(The automatic modelling options are fcst or both.Ljung-Box Q limit cannot be less than zero.Ljung-Box Q limit cannot be greater than 100.Forecast error limit cannot be less than zero.Forecast error limit cannot be greater than 100.Backcast error limit cannot be less than zero.Backcast error limit cannot be greater than 100.Overdifferencing limit cannot be less than zero.Overdifferencing limit cannot be greater than one.5bestfirstChoices are BEST or FIRST.yesnoAvailable options for outofsample are yes or no.firstallChoices are ALL or FIRST. VQ VQVQ5WQWQXQYQbZQyZQ([Q[Q{\QExpected a name or a quote or a list of names or quotes, not ""Found a NULL value; check your commas.List of names exceeds , the maximum number of elements.Expected a NAME or QUOTE not "Expected a real number or a list of real numbers, not ""Found a NULL value; check your commas.Real Vector exceeds , the maximum number of elements.Expected an real number not "Real vector exceeds Expected a date or a list of datesFound a NULL date; check your commas.Date vector exceeds , the maximum number of elements.Expected a date not ""gtedit.f(a)(' ERROR: Expected to find observation ',i4,':',i2, ' of series ',a,/, ' not ',i4,':',i2,'. Check input file and ', 'format.',/)(/,' ERROR: Problem reading ',a,'.'/, ' Too many observations in file.',/)(/,' ERROR: Problem reading ',a,'.'/, ' Check your input file and format.',/)maxitermaxnlitertolnltolparmsexactoutofsampleprintsavesavelogfilefixstepkremoveconstant(Overall tolerance is smaller than machine precision(' Make larger than ',e10.3)Nonlinear tolerance is smaller than machine precisionfixedestimatedChoices are fixed or estimatedMust specify all ARMA parameters to evaluatearmamanoneChoices are ARMA, MA, or NONE (conditional)yesnoAvailable options for outofsample are yes or no.9Cannot specify a model file when a regARIMA model is specified inthe arima and/or regression specs.nochangenonearmaregallAcceptable entries are nochange, none, arma, reg or all.Step size of numerical derivatives cannot be less than zero.Penalty term for EIC cannot be lessthan or equal to zero.Choices for removeconstant are yes and no.~Q~Q~QLQQQbQKQQQ-QDQ!QȆQ]QQgtestm.fexcludemaxleadprobabilityprintsavemaxbacklognormal(Too many forecasts specifiedCoverage probability must be strictly between 0 and 1.VToo many backcasts specifiedyesnoAvailable options for lognormal are yes or no.QQQ`QQ Q$QQ8OLDdata1r2r1l2lcansimdatevaluex12savecstramocansim2cs22l2freecommadatevaluecommafreegtfldt.f(/,' ERROR: Problem reading ',a,' using format=',a,';', /,' the program expects a Fortran format.', /,' Check your input file and format.',/)Cannot use the tramo format to read in user-defined regressors.Seasonal period given in series spec does not match seasonal period of series as defined in .Cannot use X-11 formats to read in user-defined regressors.Can only use X-11 formats to read monthly or quarterly data. ***Must have series name to use X-11 format***Starting date in series spec does not match starting date of series as defined in (/,' ERROR: Input series is empty.',/)gtfrcm.f(a)(/,' ERROR: Problem reading ',a,'.'/, ' No observations found in line ',i3,'.',/, ' Only use format="freecomma" when there are ', 'commas in data file.',/)(/,' ERROR: Problem reading ',a,'.'/, ' Too many observations in file.',/)(/,' ERROR: Problem reading ',a,'.'/, ' Check your input file and format.',/)gtfree.f(/,' ERROR: Problem reading, ',a,'.'/, ' Check that file has only correctly formatted real numbers.',/)(fP8O User-defined 04HARIMA Model(0,0,0) #@@dseriestransformidentifyregressionarimaautomdlestimateoutliercheckforecastx11historyslidingspanscompositex11regressionseatspickmdlforcemetadataspectrumCannot specify regression variables when a model file is given.Cannot specify arima and automdl spec in the same input file.Cannot specify arima and pickmdl spec in the same input file.Cannot specify arima spec if model is read in from the file argument of the estimate spec.Cannot specify automdl and pickmdl spec in the same input file.Cannot specify automdl spec if model is read in from the file argumentNeed to specify a series to identify outliersNo component series were specified for composite adjustment.Error(s) were found while executing the spec file(s) of component series used for this composite adjustment. The direct and indirect seasonal adjustment of the total series will not be performed.Cannot specify pickmdl spec if model is read in from the file argumentERROR: Series for analysis not specifed; a valid series or composite spec is required.?ERROR: Cannot set seasonal adjustment mode when automatic transformation selection is done.Program will not read model file until input errors are corrected.(/,' ERROR: ',a,' prior adustment requested in ', 'transform spec',/, ' which conflicts with inclusion of leap year ', 'prior adjustment implied ',/, ' from variable=td in regression spec (with log ', 'transformation). ',/, ' Take out adjust=',a,' in the transform spec ', 'or change td in the',/, ' variables argument of the regression spec.',/)Length-of-monthlomLength-of-quarterloqLeap yearlpyearmonth quarter(/,' ERROR: ',a,' prior adustment requested in transform ', 'spec',/, ' which conflicts with inclusion of length-of-',a, ' prior adjustment',/, ' implied from variable=td in regression spec ', '(with log transformation',/, ' and type=trend in x11 spec). Take out adjust=', a,' in the transform',/, ' spec or change td in the variables argument of', ' the regression spec.')(/,' ERROR: ',a,' prior adustment requested in transform', ' spec',/, ' which conflicts with inclusion of lpyear ', 'regression variable from ',/, ' variable=td in regression spec (with no ', 'transformation). ',/, ' Take out adjust=',a,' in the transform spec ', 'or change td in the',/, ' variables argument of the regression spec.',/)lom loq (/,' ERROR: ',a,' prior adustment requested in', 'transform spec',/, ' which conflicts with inclusion of ',a, 'regression variable from',/, ' variable=td in regression spec (with no ', 'transformation and',/, ' type=trend in x11 spec). Take out adjust=',a, ' in the transform spec or',/, ' change td in the variables argument of the', ' regression spec.',/)WARNING: No observations should be excluded from forecasting when a seasonal adjustment is done.ERROR: Seasonal period must be 4 or 12 if a seasonal adjustment is done.('(sp,e',i2.2,'.',i2.2,')')ERROR: If the seasonal period is less than 4, the user must specify the decay rate for TC outliers.WARNING: Must specify either the x11 or seats spec when the force spec is specified. Options from force spec ignored.WARNING: Spectrums are only generated for monthly series.(Q(Q4QQ߻QQQWQQQQQQ,QQQcQdQ7QQ Q+Qgtinpt.fffffff?feExpected a real number or a list of real numbers, not ""Number of initial values must equal sum of all the diffarma parameters in all the factors.Expected an real number not ")OLDsaved model fileregressionarimaUser-definedkeysvalues( Keys specified in metadata spec cannot contain spaces.:Keys specified in metadata spec cannot contain colons.keyFewer keys () than values () specified in metadata spec.Fewer values () than keys (Key values must be unique..d.Dgtmtfl.f(/,' ERROR: Enter ',a,' metafile name without "',a, '" file extension.')data.dta(' ')OLDdata metafile.m.Minput.mtainput metafile(a)(' WARNING: Number of series in data metafile exceeds ', 'program limit.',/ ' Only the first ',i5,' series will be processed.')'(' WARNING: Number of spec files in metafile exceeds ', 'program limit.',/ ' Only the first ',i5,' series will be processed.')(/,' ERROR: Closing quotation mark not found in this ',a, ' metafile.', /,' Correct the metafile and rerun ',a,'.')(/,' ERROR: The first entry in each line of a',a, ' metafile must be left ', /,' justified. Correct the metafile and rerun ',a, '.') datan input(/,' ERROR: Read error encountered in ',a,'metafile ',a,'.')a data an input Expected a NAME, QUOTE, or list of either, not an empty string.Values for this argument cannot be longer than characters.Expected a NAME or a QUOTE or a list of either, not ""Found a NULL value; check your commas.List of names exceeds , the maximum number of elements.?Expected a NAME or QUOTE not "8 typesmethodcriticallsrunspanprintsavetcratecriticalalphadefaultcriticalalmostsavelognoneaolstcall(Choices of outlier types to identify are NONE, AO, LS, TC, and ALLaddoneaddallChoices are ADDONE or ADDALLLsrun must be less than or equal to seven.Need two dates for the span or use a comma as a place holder.Span not within the seriesoutlier test spanSeriesSpan not within the model spanModel spanGCannot specify tcrate in both the regression and outlier specsValue of tcrate must be between 0 and 1.Value of criticalalpha must be between 0 and 0.10.ljungcorrectedChoices are ljung or correctedValue of almost must be greater than 0.!R!R"R#R:$R$RA'RX'Ro'Rs(R0)R)R*RExpected regression variable name or "(" but found ""Found a NULL value; check your commas.Expected regression variable name or ")" but found ")Expected a date not ""feExpected a real number or a list of real numbers, not ""Expected an real number not ")(estimatessadjlagstrendlagsfstepstartendtablefixmdltransparentrefreshoutlieroutlierwintargetprintsavesavelogfixregx11outlierfixx11regadditivesatransformfcst sadjseasonalsadjchngaicfcsttrendtrendchngarmatdChoices of estimates are sadj, seasonal, sadjchng, trend, trendchng, aic, fcst, arma, and td.Entries for sadjlags must be greater than zero.Entries for trendlags must be greater than zero.Entries for fstep must be greater than zero.Entries for fstep cannot exceed the maximum value specified for maxlead.yesnoAvailable options for fixmdl are no or yes.Available options for transparent are no or yes.Available options for refresh are no or yeskeepremoveautoAvailable options for outlier are remove, keep or auto.Cannot specify both remove and keep for the outlier argument.Value of outlierwin must be an integer greater than or equal to zero.Available options for fixx11reg are no or yes.differencepercentAvailable options for additivesa are difference or percent.Available options for transformfcst are no or yes.concurrentfinalAvailable options for target are concurrent or finalAvailable options for x11outlier are no or yes./tdholidayuseroutlierAvailable options for fixreg are td, holiday, or user.(/,' WARNING: Need to specify revisons history for ', 'seasonal adjustments in all ',/, ' components of a composite adjustment to ', 'get a revisions history of the',/, ' indirect seasonally adjusted series.')(/,' WARNING: Starting date of revisons history ', 'analysis must be specified for all',/, ' components of a composite adjustment to', ' get a revisions history of the',/, ' indirect seasonally adjusted series.')(/,' WARNING: Starting date of revisons history ', 'analysis must be the same for all',/, ' components of a composite adjustment to', ' get a revisions history of the',/, ' indirect seasonally adjusted series.')(/,' Edit all input specification files ', 'to correct this and rerun the ',/, ' metafile.')l7Rl7R8R9RA:R;R\;R;RbR[ARBRBRBRBR BRU?R@R@Rgtrvst.f(printsavesavelogappendfcstnoadmissimeanqmaxoutepsphixlrmodepsivmaxithplanhpcyclestatseastabtablesbiasfiniteprintphtrf/WXyesnoAvailable options for appending forecasts are yes or no.Available options for noadmiss are yes or no.Available options for imean are yes or no.Invalid limit for Ljung-Box Q.Limit for Ljung-Box Q must be > 0.Invalid limit for out.Out must be either 0, 1, or 2.Epsphi must be greater than or equal to zero.Xl must be greater than or equal to 0.5 and less than or equal to one.Rmod must be greater than or equal to zero and less than or Epsiv must be greater than zero.Invalid value for maxit.Value for maxit must be > 0.Hplan must be greater than zero.Available options for hpcycle are yes or no.Available options for statseas are yes or no.dInvalid limit for bias.Bias must be either -1, 0, or 1.Available options for finite are yes or no.Invalid limit for printphtrf.printphtrf must be either 0 or 1.IRIRIR,IRCIRIRJRJKRKRLRQMRNRNROR2PRPRQR3RRRRXSRTR&startdifferencetypeseriessiglevelpeakwidthmaxaraltfreqaxisprintsavesavelogsaveallfreqdecibellocalpeakstartdiffshowseasonalfreqtukey120logqs(yesfirstnoAvailable options for difference are yes, no or first.arspecperiodogramAvailable options for spectrumtype are periodogram or arspec.originaloutlieradjoriginaladjoriginalmodoriginala1a19b1e1Improper entry found for the spectrumseries argument. Valid entries for spectrumseries are a1, a19, b1, e1, original, outlieradjoriginal, adjoriginal, or modoriginal.Max order for AR spectrum must be between 1 and 30, inclusiveVisual signifcance criteria must be greater than zero.Spectral peak width must be between 1 and 4, inclusiveyesnoAvailable options for showseasonalfreq are yes or no.Available options for altfreq are yes or no.[ :samedifferentdiffAvailable options for axis are same, diff or difference.Available options for saveallfreq are yes or no.Available options for decibel are yes or no.Localpeak must be greater than or equal to zero.Available options for startdiff are yes or no.Available options for logqs are yes or no.Available options for tukey120 are yes or no.Spectrum starting date not validStarting date of spectral plots is before start of series.Starting date of spectral plots is after end of series.URUR VRVRWR2YRYRXR[R\R[R[R[R\Rq]R ^R^RfZRi_R`Rgttrmo.f (/,' ERROR: Problem reading , ',a,'.'/, ' Too many observations in file.',/)(/,' ERROR: Problem reading ',a,'.', /,' Check your input file and format.',/)(/,' ERROR: End of file encountered while reading ',a,'.', /,' Check your input file and format.',/)gtx11d.f('(12f6.',i1,',i2,a6)')('(6f12.',i1,',/,6f12.',i1,',i2,a6)')('(a6,i2,12f6.',i1,')')('(a6,i2,6f12.',i1,',/,8x,6f12.',i1,')')('(a8,i4,6f11.',i1,',2x,/,12x,6f11.',i1,',2x)')('(a8,i2,10x,12e16.10,18x)')('(a8,i4,12x,12e16.10,13x)')('(4(12x,f6.',i1,'),i2,a6)')('(4f12.',i1,',24x,i2,a6)')('(a6,i2,4(12x,f6.',i1,'))')('(a6,i2,4f12.',i1,')')('(a8,i4,4f11.',i1,',2x)') (' ERROR: Expected to find year ',i4,' of series ',a, ' not ',i4,'.',/,' Check input file and format.',/)(/,' ERROR: Problem reading ',a,'.',/, ' Check input file and format.',/)(/,' ERROR: Cannot find series ',a,' in file ',a,'.',/, ' Check series name, input file, and format.',/)8gtx12s.f(/)(' ERROR: Expected to find observation ',i4,':',i2, ' of series ',a,/, ' not ',i4,':',i2,'. Check input file and ', 'format.',/)(/,' ERROR: Problem reading , ',a,'.',/, ' Too many observations in file.',/)(/,' ERROR: Problem reading , ',a,'.'/, ' Check your input file and format.',/)PH4 $variablesuserdatastartfileformatbprintsaveusertypesigmacriticalumdataumstartumfileumformatumnameoutliermethodaictesttdpriornoapplyholidaynonlineastermeansforcecalspanoutlierspanumprecisionaicdiffsavelogumtrimzerocenteruserreweightcriticalalphadefaultcriticalprioralmost (Getting data from a fileAlready have user regression tdtdstockeasterlaborthanksaoholidaysceasteruserImproper entry for usertype. See Section 7 of Reference Manual.Trading day sigma limit must be greater than zero.Critical value for outlier detection must be greater than zero.Getting mean from a file.Already have user effect mean.@addoneaddallChoices are ADDONE or ADDALLtdtdstocktd1coeftdstock1coefeasteruserChoices for aictest are td, tdstock, td1coef, tdstock1coef, user, and easter.Can only specify one type of trading day in aictest.Must have seven prior trading day weights.tdholidayChoices are TD or HOLIDAY.yesnoChoices for holidaynonlin are yes or no.Choices for eastermeans are yes or no.Choices for forcecal are yes or no.Need two dates for the irregular component regression span or use a comma as a place holder.Need two dates for the span or use a comma as a place holder.Number of input decimals must be between 0 and 5, inclusive.yesspannoChoices for umtrimzero are yes, span or no.meanseasonalChoices for centeruser are mean and seasonal.Choices for reweight are yes or no.Value of criticalalpha must be between 0 and 0.10.ljungcorrectedChoices are ljung or corrected.Choices for prior are yes or no.Value of almost must be greater than 0.(' ERROR: Number of initial values is not the same as ', 'the number of regression',/,' variables.')Irregular component regression span not within the span of available data.irregular component regression spanspanSpan not within the seriesoutlier test spanSeriesSpan not within the model spanModel span(/,' ERROR: Need to specify both user-defined ', 'irregular component',/, ' regression variables and X-matrix.')(/,' ERROR: Number of user-defined X elements=',i4, /,' not equal to a multiple of the number of ', 'columns=',i3,'.',/)span of the datauser-defined regression variablesUser-defined HolidayUser-defined(/,' ERROR: User-defined mean can only be specified if ', /,' user defined regressors are also present.',/)user-defined mean effects(' ERROR: Cannot specify group types for user-defined ', 'irregular component',/, ' regression variables if user-defined ', 'irregular component',/, ' regression variables are not defined in the ', ' x11regression spec.')(' ERROR: Cannot specify noapply when user-defined ', 'mean is also present.')(' ERROR: Must adjust for either trading day or ', 'holiday in the x11regression spec.')`R`R#RR+RR_RRR2RIR1RՋRÌRORȍRRRR;RR$RRR]R RȕRMRՖRFR]RRØRrR RϚR{Rgtxreg.f?@0@@ @"@9@s@&@333333????hist.f(' Standard',/,' Deviations Frequency')(/,' Outlier [',69A1)#(1x)(i9,' +',69A1)(9x,' |',69A1)(/,' One ''#''=',i2,' observation[s]')(/,' Residuals with |t|>3.25')(/,' Only the first ',i3,' of the ',i3, ' extreme residuals are shown.',/)(/,' Obs t-value',/,' -----------------')(' ',a,t12,f8.2)(/,' Summary Statistics for the Unstandardized Residuals',/, ' Minimum',t21,f15.3,/,' Maximum',t21,f15.3,/,' Median', t21,f15.3,/,' Robust Std Dev',t21,f15.3)@ףp= ?@Q@?histx.f(//,' Summary Statistics for the ',a,/)(5x,'Minimum',t27,': ',5x,f10.1,/,5x,'25th Percentile', t27,': ',5x,f10.1,/,5x,'Median',t27,': ',5x,f10.1,/,5x, '75th Percentile',t27,': ',5x,f10.1,/,5x,'Maximum',t27, ': ',5x,f10.1,//,5x,'Standard Deviation',t27,': ',5x, f10.1,//)(5x,'Minimum',t27,': ',f10.2,/,5x,'25th Percentile',t27, ': ',f10.2,/,5x,'Median',t27,': ',f10.2)(5x,'75th Percentile',t27,': ',f10.2,/,3x,'->',i2, 'th Percentile',t27,': ',f10.2,'<-',/,5x,'Maximum', t27,': ',f10.2//,5x,'Standard Deviation',t27,': ',5x, f10.2,//)U(3x,'->60th Percentile',t27,': ',f10.2,'<-',/,5x, '75th Percentile',t27,': ',f10.2,/,5x,'Maximum', t27,': ',f10.2//,5x,'Standard Deviation',t27,': ',5x, f10.2,//)Z(//,' Histogram of the ',a,/)(' Absolute',/,' Differences Frequency')(' Percent',/,' Differences Frequency')(/,' Outlier [',69A1)#(1x)(3x,f7.1,' +',69A1)(4x,f6.2,' +',69A1)(10x,' |',69A1)(/,' One ''#''=',i2,' observation[s]')(/,2x,a,' considered to be outliers',/,' Time ',a,/,a)(1x,i2,':',i4,f8.2)(//, ' Number of observations considered to be outliers = ',i3,/, ' (only the first 50 were listed above)')('s3.',a,'.hinge:',8(2x,f8.3))/$??@Q@?@(@?PERT! @@holday.f(/,10X,'NO YEARS WITH EASTER BEFORE APRIL 1ST.')(/,10X,'NO YEARS WITH EASTER AFTER APRIL 16TH.')(/,10X,'NO YEARS WITH EASTER BETWEEN APRIL 2ND ', 'AND APRIL 8TH.')(/,10X,'NO YEARS WITH EASTER BETWEEN APRIL 8TH ', 'AND APRIL 15TH.')(/,10X,'NO EASTER ADJUSTMENT PERFORMED.')K hrest.f(/A/) Some initial estimates cannot be obtained for HR estimation(A/) Default values used ? _Bhtmlout.f(/,10x,"MEAN =",g16.6,/)(//17x,"AR PARAMETERS ",/)(11x,"PHI =",3f10.4)(11x,"PHI =",2f10.4)(11x,"PHI =",f10.4)(11x,'BPHI =',f10.4,/)(//,4x,'INPUT MODEL HAS A STATIONARY ', 'SEASONAL STRUCTURE',/,4x, 'INAPPROPRIATE FOR SEASONAL ADJUSTMENT.',/,4x, 'SEATS HAS CHANGED THE SEASONAL ORDERS TO :',/,47x, '(0, 1, 1)',/,4x,'This may affect forecasting.',//)(///, ' PARTIAL AUTOCORRELATIONS'/' ------------------------')(/,' ',12(2x,f7.4))(' SE',12(2x,f7.4))(/,' ',9x,'MEAN =',g16.6,/,/,' ',9x, 'SE = *******'//)(/,' ',9x,'MEAN =',g16.6,/,/,' ',9x,'SE =' ,g16.6,//)(/,' ',11x,'CORRELATION MATRIX'//)(12(5x,f6.3))(/,' ',9x,'MEAN =',g16.6,/,/,' ',9x, 'SE = *******'//)(//17x,'ARIMA PARAMETERS ',/)(11x,'PHI =',3f10.4,/,11x,'SE =', 4x,3('*****',6x))(11x,'PHI =',2f10.4,/,11x,'SE =', 4x,2('*****',6x))(11x,'PHI =',f10.4,/,11x,'SE =', 4x,1('*****',6x))(/,' ',11x,'PHI =',3f10.4)(' ',11x,'SE =',3(3x,f7.4))(11x,'BPHI =',f10.4,/,11x,'SE =', 4x,'*****',6x)(/,' ',11x,'BPHI =',3f10.4)(' ',11x,'SE =',3x,f7.4)(11x,'TH =',3f10.4,/,11x,'SE =', 4x,3('*****',6x))(11x,'TH =',2f10.4,/,11x,'SE =', 4x,2('*****',6x))(11x,'TH =',f10.4,/,11x,'SE =', 4x,('*****'))(/," ",11x,"TH =",3f10.4)(" ",11x,"SE =",3(3x,f7.4))(11x,'BTH =',f10.4,/,11x,'SE =', 4x,'*****',6x)(/," ",11x,"BTHETA = ",3f10.4)(' ',11x,'SE = ',3x,f7.4)(3x,'Decomposition : Properties')(17x,'Convergence', 23x,'Signif. Stoch.',21x,'DAA')(19x,'(in %)',26x,'Season. (95%)')(11x,'1Y',17x,'5Y')(8x,'TC',8x,'SA',8x,'TC',8x,'SA', 8x,'Hist.',5x,'Prel.',5x,'Fore.',11x,'TC', 8x,'SA')(3x,'Decomposition : General')(5x,'Pread.',x,'Model',3x, 'Approx.',15x,'Model',17x,'SD(a)',4x, 'SEAS_NP(a)',5x,'Spectr.',x,'Check',2x, 'Check',5x,'Determ.')(12x,'Changed',x,'to NA',63x,'Factor', 2x,'on ACF',x,'on CCF',2x,'Comp. Modif.')(28x,'m',4x,'p',4x,'d',4x, 'q',4x,'bp',4x,'bd',4x,'bq', 48x,'TC',x,'S',x,'U',x, 'TRANS',x,'SA')(' mq=12: TD= 2.1878 rad ')(' mq=4 : TD= 0.2802 rad ')(" AT : peaks detected in AR(30)", " and using Tukey spectrum estimator")(" A- : only peaks detected in AR(30) spectrum estimator")(" -T : only peaks detected ", "using Tukey estimator spectrum")(" -- : No peaks detected in AR(30)", " nor using Tukey spectrum estimator")(6X,'Period', ' associated with a 50% gain of filter:', F10.1,' (Default value)')(6X,'Period', ' associated with a 50% gain of filter:', F10.1)(6X,'Implied value for HP LAMBDA=', F15.4) - 2.0 (//,5x,A,/,4x, ' ---------------------------------------------------------')( 3x,' REAL PART ',' IMAGINARY PART',' MODULUS ', ' ARGUMENT',' PERIOD')(2x,f11.3,4x,f11.3,5x,f11.3,4x,f11.3,5x,a4)(2x,f11.3,4x,f11.3,5x,f11.3,4x,f11.3,1x,f11.3)(//,9x,'CONCURRENT ESTIMATOR:PHASE DIAGRAM',/)(6x,'period of cycle',a,'Delay(in ',a,')') months time periods(23x,'SA series',20x,'trend-cycle')(23x,'Semi-infinite',3x,'finite',3x, 'semi-infinite',3x,'finite')(7x,a,2x,F6.1,7x,F6.1,7x,F6.1,7x,F6.1) INF 20 years cycle10 years cycle 5 years cycle 2 years cycle(6x,'period of cycle',4x,'Delay(in ',a,')')(23x,'SA series',3x,'trend-cycle')(7x,a,2x,F6.1,7x,F6.1) INF Transitory innovation variance is very small. Transitory component can be ignoredIN AN ATTEMPT TO IMPROVE SEASONAL ADJUSTMENT, NON-STATIONARITY HAS BEEN IMPOSED ON THE SEASONAL COMPONENT.THE MODEL EVIDENCES VERY WEAK SEASONALITY. ITS ESTIMATION WOULD BE ERRATIC AND THE EFFECT IS CAPTURED AS A TRANSITORY COMPONENTS.SEASONALITY IS STATIONARY(EVERY PERIOD HAS ZERO MEAN)AND MODEL MAY YIELD AN ERRATIC SEASONAL COMPONENT.SEASONAL ADJUSTMENT MAY BE IMPROVED BY SETTING "STATSEAS=1".(6X,a)(1) DECOMPOSITION OF THE TREND-CYCLE COMPONENT INTO : (10X,a) LONG-TERM TREND + CYCLECYCLE EXTRACTED FROM SA SERIESCYCLE EXTRACTED FROM ORIGINAL SERIESB (A,'(t)=K',A)ư>F a(t)(//,8x,'(1) HISTORICAL ESTIMATOR')(/,8x,A)(/,8x,'K',A,'= ',F9.6)(A,'(t|t)=Kc',A)(//,8x,'(2) CONCURRENT ESTIMATOR[',A,'(t|t)]')(/,8x,'Kc',A,'= ',F9.6)MA ROOTS of concurrent estimator('R(t|t)=Kr',A,' F')(//,8x,'(3) REVISION IN CONCURRENT ESTIMATOR', ' [R(t|t)]')(/,8x,'Kr',A,'= ',F9.6)(/,' ',i1,'PARAMETERS FIXED ')(I5,"TH")(//," ARIMA MODEL SELECTED BY REGARIMA: ", "(",i1,",",i1,",",i1,")(",i1,",",i1,",",i1, ")")(//,"SEATS ARIMA MODEL INPUT: ", "(",i1,",",i1,",",i1,")(",i1,",",i1,",",i1, ")")with meanwithout mean(/," ARMA Parameters")(11x,"PHI =",3f10.4)(11x,"PHI =",2f10.4)(11x,"PHI =",f10.4)(11x,"THETA =",3f10.4)(11x,"THETA =",2f10.4)(11x,"THETA =",f10.4)(11x,"BTHETA= ",f10.4,/)(i4,3x,a,x,i2,8x,i2,x,4(i4,4x),x,i2,x,3(i2), 2x,3(i2,x),2x,4(i4,4x),8x,i2)(f7.4)(3x,"0",3x)*(i4,3x,a,x,i2,x,f9.2,x,4(a,x),2x,i1,2x,2(i1,x),i2, 2x,3(i1,2x),x,4(a,x),g12.4)(/,' ',12f9.4)(' SE',12f9.4)( //,' THE LJUNG-BOX Q VALUE IS ',f10.2,' AND IF RESIDUALS ', 'ARE RANDOM IT SHOULD BE DISTRIBUTED AS CHI-SQUARE (',i2,')')( /,' PART 2 : DERIVATION OF THE MODELS ', 'FOR THE COMPONENTS AND ESTIMATORS',/ ' ----------------------------------', '---------------------------------',//)(/,' SERIES TITLE: ',a)( /,' MODEL PARAMETERS'/' (',i1,',',i1,',',i1,')(',i1,',',i1,',' ,i1,')'//' PARAMETER VALUES : COEFFIC. OF POLYNOMIALS IN B', ' OF THE MODEL (TRUE SIGNS)')(/,' THETA PARAMETERS')(' ',16(f5.2,2x))(/,' BTHETA PARAMETERS')(/,' PHI PARAMETERS')(/,' BPHI PARAMETERS')('OVERALL TEST FOR IDENTIFIABLE SEASONALITY')('(Convination of significance of autocorrelation ', 'for seasonal lags, ')('non parametric, and spectral test)')(" 1 : IDENTIFIABLE SEASONALITY DETECTED.")(" 0 : NO IDENTIFIABLE SEASONALITY IS DETECTED.")(x,"IN SEASONALLY ADJUSTED SERIES :",x,I1)(x,"IN TREND-CYCLE COMPONENT : ",x,I1)(x,"IN IRREGULAR COMPONENT : ",x,i1)("(",I2,"X,'Stochastic Component: ", A,"')")(A,I2,A,A)(x,5x,'Seasonal frequencies(cycles per year and TD freq.(rad.)')(A,I2,A)x,5x,e'SEAS. freq. TD(rad.)')(A,I2,A,I2,A)x,4x,('-'),2x,7('-'))(A,I2,A,I1,A)x,(A,x)) TD (A,I1,A)(i4,3x,a,x,(A,5x))(7x,(//,4x,'ARIMA MODEL FOR ESTIMATORS',/)(4x, 'Innovation are these in observed series (a(t))')(//,6x,I1,'. SA SERIES [n(t)]',/)N(//,6x,I1,'. TREND-CYCLE COMPONENT [P(t)]',/)P(//,6x,I1,'. SEASONAL COMPONENT [S(t)]',/)STDsTD.stochasticCTRANSITORY(//,6x,I1,'. ',A,' [',A,'(t)]',/)(//,6x,I1,'. IRREGULAR COMPONENT [U(t)]',/)U6572012/11/28 12:09:23Revision: Build: .sms(2x,'Date : ',A)-:(2x,a,i7)Series in file : Series processed with SEATS : Series processed with X-11 : Series not seasonally adjusted : Series processed :(a) *(f6.3) *(i2)(/,2x,'Input Parameters:')(2x,"rmod=",A6,2x,"xl=",2x,A6,2x)(2x,"posbphi= ",A2,2x,"stochtd= ",A2,2x,"statseas= ",A2)(/,/,4x,a)TABLE A : GENERAL --------------------------(34x,'# of series',4x,'%')(2x,50("-"))(2x,a,i7,4x,f6.2)Model changed by SEATS Approximate (NA decomposition) With seasonal component With Transitory Component With Stochastic TD TABLE B: CHECKS(42x,"# of series",4x,"%")(2x,58("-"))Fail Spectral factorization Fail check on ACF Fail check on CCF (2x,a,/,2x,a,i7,4x,f6.2)Unstable seasonality (too large innovation variance) Unreliable estimation of seasonality(too large estimation variance) Revisions in SA series are too large Seasonality detected but not significant Bias in level of SA series is too large TABLE C: RESIDUAL SEASONALITY IN SA SERIES ------------------------------------------(35x,"# of series",4x,"%")(2x,51("-"))Autocorrelation function evidence Non-Parametric evidence Espectral evidence (//,a," model has no admissible decomposition",//)(//,a," model has changed.",/, " The model is approximated to (",i1,",",i1,",",i1, ")(",i1,",",i1,",",i1,")",//)(" Model changed to (",i1,",",i1,",",i1,")(",i1, ",",i1,",",i1,")")\ErrorLog.txtL(4x,"n",5x,"TITLE",23x,"Description")(33x,a)(i7,2x,a22,4x,a)(//,/,' ',11x,'PARAMETER ESTIMATES'/)MA(Q)AR(P)Linealized Series (/,' TRANSFORMED SERIES')(/,' NONSEASONAL DIFFERENCING D=',i2,/, ' SEASONAL DIFFERENCING BD=',i2)(//,' DIFFERENCED SERIES') (/,' SERIES HAS BEEN MEAN CORRECTED')(/,' DIFFERENCED AND CENTERED SERIES')(/, ' DIFFERENCED AND CENTERED TRANSFORMED SERIES')(/,1x,'MEAN OF DIFFERENCED SERIES=',d12.4)(/,' MEAN SET EQUAL TO ZERO')(//,' VARIANCE OF Z SERIES = ',d14.4)(/,1x,'VARIANCE OF DIFFERENCED SERIES = ', d14.4)(///, ' AUTOCORRELATIONS OF STATIONARY SERIES',/, ' -------------------------------------')AUTOCORRELATIONS OF STATIONARY SERIESSTATIONARY SERIES( /////,' MODEL FITTED'//' NONSEASONAL P=',i2, ' D=',i2,' Q=',i2)(/////,' MODEL'//' NONSEASONAL P=',i2, ' D=',i2,' Q=',i2)(' SEASONAL BP=',i2,' BD=',i2, ' BQ=',i2)(' PERIODICITY MQ=',i3)Y(//,8x,'ARIMA MODEL FROM regARIMA HAS BEEN', /,5x,'MODIFIED TO SATISFY SEATS CONSTRAINTS',/)(//," FIRST MODEL THAT ENTERS ", "THE DECOMPOSITION: ")(//," ARIMA MODEL SELECTED BY regARIMA: ")(//," ARIMA MODEL SELECTED: ")("(",i1,",",i1,",",i1,")(",i1,",",i1,",",i1, ")")(///,27x,'ROOTS OF ',A,' POLYNOMIAL')(/,' '//' EXTENDED RESIDUALS')(/,' ','STUDENTIZED EXTENDED RESIDUAL OF',f8.4, ' AT T=',i3,4x,'(',i2,1x,i4,')')( ///,' ',' TEST-STATISTICS ON EXTENDED RESIDUALS',/ ' -------------------------------------',///, ' MEAN=' ,d12.4,/' ST.DEV.=',d12.4,/' OF MEAN',/ ' T-VALUE=',f8.4,//' NORMALITY TEST=',g14.4, 4x,'( CHI-SQUARE(2) )',/' SKEWNESS=',f8.4, 10x,'( SE =',f8.4,' )'/' KURTOSIS=',f8.4,10x, '( SE =',f8.4,' )'//' SUM OF SQUARES=',d12.4// ' DURBIN-WATSON=',f8.4,//' STANDARD DEVI.=',d12.4/ ' OF RESID.',/' VARIANCE=',d12.4,/ ' OF RESID.')(//,2x,'NON-PARAMETRIC TEST FOR RESIDUAL ', 'SEASONALITY (FRIEDMAN) SEAS_NP = ',f9.2,/,2x, ' ASYMP. DISTRIBUTED AS CHI-SQUARE(',i2,')')('Critical value 99%: ',f9.2)('Critical value 95%: ',f9.2)( ///' AUTOCORRELATIONS OF EXTENDED RESIDUALS'/ ' --------------------------------------')ACF ResidualsEXTENDED RESIDUALS(6x, 'EVIDENCE OF EXTENDED RESIDUALS CORRELATION :',2x,a)LARGEMODERATE(6X,'EVIDENCE OF NON-NORMALITY')(6X,'EVIDENCE OF ASYMETRY POSITIVE')(6X,'EVIDENCE OF ASYMETRY NEGATIVE')(6X,'EVIDENCE OF EXCESS KURTOSIS')(/,' APPROXIMATE TEST OF RUNS ON EXTENDED RESIDUALS',/, ' ----------------------------------------------')(/,' NUM.DATA=',i4,/' NUM.(+)=',i4,/' NUM.(-)=',i4)(' T-VALUE=',g16.3)Residuals (///,' AUTOCORRELATIONS OF SQUARED EXTENDED RESIDUALS',/ ' ---------------------------------------------')ACF sqd ResidualsSQUARED EXTENDED RESIDUALSYES(6X,'EVIDENCE OF NON-LINEARITY :', 2X,A)(6x, 'EVIDENCE OF SEASONAL NON-LINEARITY :',2x,a)(/,' BACKWARD RESIDUALS')( /,' ','NUMERATOR OF THE MODEL (TOTAL MOVING AVERAGE ', 'POLYNOMIAL)')( ' ','---------------------------------------------', '-----------')(12f8.4)(///,' FACTORIZATION OF THE TOTAL AUTOREGRESSIVE POLYNOMIAL' ,/,' -----------------------------------------------------',/ )(/,' ','STATIONARY AUTOREGRESSIVE TREND-CYCLE')#( 'WARNING:',/,'Stationary Autoregressive ',a, ' MAY HAVE UNIT ROOT')Trend-Cycle(/,' ','NON-STATIONARY AUTOREGRESSIVE TREND-CYCLE')"( 'WARNING:',/,'Non-Stationary Autoregressive ',a, ' Component MAY HAVE UNIT ROOT')Trend(/,' ','AUTOREGRESSIVE TREND-CYCLE')(' ','--------------------------')(/,' ','STATIONARY AUTOREGRESSIVE ',A,' COMPONENT')$(/,' NON-STATIONARY AUTOREGRESSIVE ',A,' COMP')%(/,' ','AUTOREGRESSIVE ',A,' COMP.')(' ','------------------------------')(/,' ','STATIONARY AUTOREGRESSIVE SEASONAL COMPONENT')Seasonal(/,' ','NON-STATIONARY AUTOREGRESSIVE SEASONAL', ' COMPONENT')~(/,' ','AUTOREGRESSIVE SEASONAL COMPONENT')(' ','---------------------------------')( /,' ','STATIONARY AUTOREGRESSIVE ', 'SEASONALLY ADJUSTED COMPONENT')( /,' ','NON-STATIONARY AUTOREGRESSIVE ', 'SEASONALLY ADJUSTED COMPONENT')(/,' ','AUTOREGRESSIVE SEASONALLY ADJUSTED COMPONENT')(' ','--------------------------------------------')( /,' ','TOTAL DENOMINATOR (TOTAL AUTOREGRESSIVE ','POLYOMIAL)')( ' ','----------------------------------------','----------')WARNING: DIMENSION PROBLEM2.1878SPECTRAL DIAGNOSTICS--------------------('A. STOCHASTIC SEASONAL AND TRADING DAY SPECTRAL PEAKS')(3x,'Stochastic seaonal and trading day spectral peaks')(36x,'Frequency (cycles per yer)',14x,'TD')(29x,6(A7),2x,'(',A6,' rad)')(1x,a,4x,6(A2,5x),3x,A2)Seasonally adjusted seriesTrend-Cycle component Irregular component (1x,a,' : ',a)ATpeaks detected in AR(30) and using Tukey spectrum estimatorA-only peaks detected in AR(30) spectrum estimator-Tonly peaks detected using Tukey estimator spectrum--No peaks detected in AR(30) nor using Tukey spectrum estimatorB. STOCHASTIC SEASONALITY: SPECTRAL EVIDENCE 1 : EVIDENCE OF RESIDUAL SEASONALITY. 0 : NO EVIDENCE OF RESIDUAL SEASONALITY OR EVIDENCE IS TOO WEAK.(x,a,1x,A1)IN SEASONALLY ADJUSTED SERIES :IN TREND-CYCLE COMPONENT : IN IRREGULAR COMPONENT : C. TRADING DAY EFFECT: SPECTRAL EVIDENCE 1 : EVIDENCE OF RESIDUAL TRADING DAY EFFECT 0 : NO EVIDENCE OF RESIDUAL TRADING DAY EFFECT OR EVIDENCE IS TOO WEAK.(4x,'Detected a Spectral peak in ',A ' for the TD frequency ')(I1,"PI/6")(4x,'There is a Spectral peak in ',A, ' for the Seasonal frequency : ',A6)(4x,'There is a Spectral peak in ',A, ' for the Seasonal frequencies : ',A40)LONG TERM TRENDSA series without BCSeries without BC PART 6 : ESTIMATION OF THE CYCLE -------------------------------- MODIFIED HODRICK-PRESCOTT FILTER(/)(6x,a)"FICTICIOUS" MODEL FOR WK IMPLEMENTATION OF FILTER(2) ARIMA ModelsStochastic m(t):Stochastic Cycle c(t):(3) Std of innovations(6X,A,G15.4)Long Term Trend: Business Cycle: (4) FINAL ERRORS The business Cycle Component got unit roots in the AR part, so the variance of final error of Business Cycle and is infinite. The AR part of Business Cycle component got roots too close to unity to proper calculate the final error variance(' Var(final error of ',A,' Component)= ',t55, G15.4,' in units of Va')Business CycleSPECTRUM OF CYCLE, rendmod.m=(3x,"n",8x,"Title",12x,"D",x,"PHIP(1)",x,"PHIP(2)",x, "PHIP(3)",x,"PHIP(4)",2x,"THP(1)",2x,"THP(2)",2x,"THP(3)", 2x,"THP(4)",2x,"THP(5)",2x,"THP(6)",2x,"THP(7)",2x, "Stand.Innov.Var")/samod.m?(A,2x,"PHIN(",i1,")")(A,x,"PHIN(",i2,")")(A,2x,"THN(",i1,")")(A,x,"THN(",i2,")")(A,2x,"Stand.Innov.Var")(3x,"n",8x,"Title",12x,"D",A)/seasmod.m>(A,x,"PHIS(",i1,")")(A,x,"PHIS(",i2,")")(A,2x,"THS(",i1,")")(A,x,"THS(",i2,")")(3x,"n",8x,"Title",12x,"S",A,2x, "Stand.Innov.Var") ransmod.m@(" PHIC(1)")(A,2x,"PHIC(",i1,")")(A,x,"PHIC(",i2,")")(A,2x,"THC(",i1,")")(A,x,"THC(",i2,")")(3x,"n",8x,"Title",11x,A,2x,"Trans.Innov.Var",3x, "Irreg.innov.Var").tbs$.psie%(/,58x,'PROGRAM SEATS+',//, 42x,'(based on program SEATS,', ' Victor Gomez and Agustin Maravall, 1996)',//, 38x,'Developed at the Bank of Spain ', 'by Gianluca Caporello and Agustin Maravall,',/, 38x,'with programming support from', ' Domingo Prez Caete and Roberto Lpez Pavn.',//, 36x,'Help from Gabriele Fiorentini (1990 - 1991)', ' and Christophe Planas (1992 - 1994) ',/, 36x,'is also acknowleged.',//, 46x,'VERSION: 1.0 (',A,')',//)(/,38x,'PROGRAM SEATS+',//, 12x,'(based on program SEATS,', ' Victor Gomez and Agustin Maravall, 1996)',//, 8x,'Developed at the Bank of Spain ', 'by Gianluca Caporello and Agustin Maravall,',/, 8x,'with programming support from', ' Domingo Prez Caete and Roberto Lpez Pavn.',//, 6x,'Help from Gabriele Fiorentini (1990 - 1991)', ' and Christophe Planas (1992 - 1994) ',/, 6x,'is also acknowleged.',//, 16x,'VERSION: 1.0 (',A,')',//)DT! @f@h㈵?@-q=@#"@#@@ \X@iddiff.f(/,' ARIMA Estimates ',a,' for ',a,' Identification : ', 'Model No. ',i2,/)(H-R)Unit Root(/,' ERROR: Unable to set up ARIMA model for unit root ', 'testing procedure',/, ' for the reason(s) given above.')(/,' Estimation error found during unit root testing ', /,' procedure while fitting inital regARIMA model to the', ' series.')(exact mle)(conditional)(/,' ERROR: Estimation failed to converge during the ', 'automatic model',/ ' identification procedure.')MbP?(/,' ',a,' difference order reset to ',i1,', the limit ', 'specified in the',/,' maxdiff argument.')RegularSeasonal(/,' Results of Unit Root Test for identifying orders', ' of differencing:')( ' ',a,' difference order : ',i3)Constant8(/,' Mean ',a,' significant.')is notisRQ?Gz?Mb`?+?Q?RQ??{Gz?(\?)\(?Q?{Gz?ffffff@Gz?@ffffff@ERROR: Not enough data to perform maximum order of differencing specified in the diff and sdiff arguments of the identify spec.Constant(/,' WARNING: For calculating the ACF''s and PACF''s ', 'requested from the identify',/, ' spec, a sample mean adjustment has been ', 'used in place of the',/, ' effect of the constant regressor ', 'specified in the regression spec.',/)?K $&(/,' Differencing: none')(/,' Differencing: Seasonal Order=',i1)(/,' Differencing: Nonseasonal Order=',i1)(/,' Differencing: Nonseasonal Order=',i1, ', Seasonal Order=',i1)#idmdl.fE- t(AO)t(LS)t(TC)Automatically Identified Outliers8Y(/,' ERROR: ARMA parameter roots maybe inside of the ', 'unit circle.', /,' Use conditional estimates as starting ', 'values.')(/,' ERROR: Cannot perform automatic outlier ', 'identification if the robust ', /,' mean square error of the residuals is zero.')(/,' Check the x11regression options specified', ' in the input specification',/,' file.',/)(/,' Check the regARIMA model specified in the', ' input specification',/,' file.',/) (' ',a)(//,' Forward addition pass',i3,/,' ',26('-'),/, ' Robust root mse ',1p,e10.2,/, ' Normal root mse ',e10.2)(' Outlier ',a:,' ',a:,' ',a:,' ',a)(/,' NOTE: Unable to test ',a, ' due to regression matrix singularity.',/, ' The effect of this outlier is already ', 'accounted for by other regressors ',/, ' (usually user-specified or ', 'previously identified outliers).')(f14.2,a1)(' ',a,t24,4(' ',a15))i(a,':',4(1x,e22.15))+(//,' The following time series values might ', 'later be identified as outliers',/' when data ', 'are added or revised. They were not identified ', 'as outliers',/,' in this run either because ', 'their test t-statistics were slightly below',/, ' the critical value or because they were ', 'eliminated during the backward',/,' deletion ', 'step of the identification procedure, when a non', '-robust ',/,' t-statistic is used.')(' ',a,//)(/,' Add',/,' +',a22,a15,3(' ',a15))AO Outlier t-valuesLS Outlier t-valuesTC Outlier t-values(' No more outliers identified')B(/,' ERROR: regARIMA model estimation in outlier ', 'identification procedure did',/, ' not converge.')(//,' Backward deletion pass',i3,/,' ',66('-'),/,t30, 'Parameter',t47,'Standard',/,' Variable',t31,'Estimate', t50,'Error',t61,'t-value',/,' ',66('-'))(' -',a,t23,f16.4,f16.5,f13.2)AO onlyLS onlyAO and LSTC onlyAO and TCLS and TCAll types(/,' No ',a,' outliers identified',/)(' Largest outlier t-value : ',f10.5,' (',a,')')Final AO Outlier t-valuesFinal LS Outlier t-valuesFinal TC Outlier t-valuesL(1000a)date---------------------------d*(a,i5)addoutlier: deloutlier: (a,f15.7)almost: nalmostout: almostoutlier$(%5Eidotlr.f/$?=J@`Y8(a,': ',a) X-13A-S model samodelogarithmic seasonal adjustmentadditive seasonal adjustmentx13mdlinitdg.finpter.f(/,' Line',i5,': ',/,' ',a)(/,' Line',i5,': ',a)(a)^WARNINGERROR()(' ',a,': ',a)(' ',a,': ',a,/,' ',a,' ',a)(a,' Problem was discovered on line',i5,', column ',i4,'.') insptr.f(/,' ERROR: Too many elements for vector.',/)(/,' ERROR: No room to add new element to vector.',/)(/,' ERROR: Not able to insert element in position',i4,/, ' of a',i3,' long vector.',/)Cannot process empty input specifications file.?@?invfcn.f(' ERROR: Cox-Box routine-y(',i5,')=',f16.8,'and 1/lam=', f5.2,'.')?(fixed) itoc.f Error: Can't write in spaces?itrerr.f(/, ' ***********************************************************************')(/,' ERROR: Estimation failed to converge -- maximum ',a, ' reached',/,' during sliding spans analysis.')(/,' ERROR: Estimation failed to converge -- maximum ',a, ' reached',/,' during history analysis.')(/,' ERROR: Estimation failed to converge -- maximum ',a, ' reached.')(/,' Parameter values and log likelihood at ', 'last iteration follow.',//)(' Rerun program trying one of the following:',/, 10x,'(1) Allow more iterations (set a larger value of ', 'maxiter).')(10x,'(2) Try a different model.',//,1x,'See ',a, ' of the ',a,' ',a,' for more discussion.')Section 5X-13ARIMA-SEATSReference Manual(10x,'(2) Fix the values of the ARMA coefficients to ', 'those obtained',/,14x, 'while estimating the full series (set fixmdl=yes)')(10x,'(2) Use initial values for ARMA parameters as ', 'given below.')(10x,'(3) Try a different model.',//,1x,'See ',a, ' of the ',a,' ',a,' for more discussion.')[ kwtest.f(/,' Nonparametric Test for the Presence of Seasonality ', 'Assuming Stability')(/,a,'Kruskal-Wallis statistic',2x,'Dgrs.freedom',2x, 'Probability level')(a,F11.4,6X,I3,7X,F9.3,'%',/)(//,a,'Nonparametric Test for the Presence of Seasonality', ' Assuming Stability')(/,a,'Kruskal-Wallis',6x,'Degrees of',4x,'Probability',/, a,'Statistic',8x,'Freedom',9x,'Level')(/,a,F11.4,9X,I3,8X,F9.3,'%',/)(a,'Seasonality present at the one percent level.')(a,'No evidence of seasonality at the one percent level.')(@Y@?8?PERT! @?ARMA ARMA?????-C6?QP450locshk.f?Length-of-MonthLength-of-QuarterLeap Year(//,' Likelihood statistics for model with ',a, ' regressors')(//,' Likelihood statistics for model without ',a, ' regressors')(' AICC(',a,')',t27,': ',f15.4)('aictest.',a,'.aicc.',a,': ',e29.15)(' AICC(no ',a,')',t27,': ',f15.4)noLength-of-8(//,' ***** AICC (with aicdiff=',F7.4, ') prefers model ',a,1x,a,' regressor *****')withwithoutlomaic.f?ERROR: X-13ARIMA-SEATS could not generate a table title (internal code #). Please send the input spec file that generated this error message, along with any data files used, to x12@census.gov.%-to- ^B 1.AA 8.AA 8.TC.AA 8.SO.AA 6.AA 7.AA 9.AA 10.AA 13.AD 10.AD 10.AD 10.ED 10.CD 10.TH 1.AA 16.AD 16.AD 16.AD 16.CD 18.AE 18.AE 18.CD 11.FFA 4.CC 16.AC 18.AC 16H.AC 16C.AC 18C.AB 1.AD 10.AD 10.AD 10.CE 18.AE 18.CD 18.AD 16.AD 16.AD 11.FFS 12.AS 12.DS 10.AS 10.AS 13.AS 13.AS 11.AS 11.DS 14.AS 14.AS 16.AS 16.AS 18.AS 18.CS 1.FS 11.FS 12.FS 10.CS 14.TCFS 14.DTCFS 11.OAS 13.OAA 1A 1.GMV 1A 18A 19B 1B 1.GA 1.CA 1C.GA 2A 2.PA 2.TA 3A 3.PA 4.DA 4.PA 8A 8.AOA 8.LSA 8.TCA 8.SOA 6A 7A 9A 10A 13C 1D 1E 1F 1B 2C 2D 2E 2B 3E 3B 4C 4D 4B 5C 5D 5E 5E 5B 6C 6D 6E 6E 6B 7C 7D 7E 7E 7B 8D 8D 8.BE 8E 8B 9C 9D 9B 10C 10D 10D 10D 10.DD 10.BD 10.SB 11C 11D 11D 11.CE 11D 12D 12D 12.BD 12.CB 13C 13D 13D 13D 13.BB 17C 17B 20C 20H 1A 16D 16D 16D 16.BD 18E 18E 18.BB 19C 19F 2F 3E 4D 8.AD 9.AE 0.GG.3G.4D 10.GD 11.GD 12.GD 13.GD 11.FD 12.FC 17.FD 11.AD 11.RE 6.AE 6.AE 6.RE 6.RD 11.CRD 11.RRD 11.FA 4B 14C 14B 15C 15B 16C 16B 18C 18B 16HC 16HB 16CC 16CB 18CC 18CR OTLRR MSRR 1R 1.SR 1.AR 2R 2.SR 2.AR 3R 3.SR 3.AR 4R 4.SR 4.AR 5R 5.SR 5.AR 6R 6.SR 6.AR 7R 8R 8.AR 9R 9.AR 9.BS 7.AS 7.AIS 7.CS 7.CIS 7.DS 7.DIS 7.ES 7.EI+L32S 7.BA 1A 3B 1B 1.GA 18A 19D 8D 9D 10D 10D 10.BD 11D 12D 13D 13E 1E 2E 3E 5E 5E 6E 6E 6.AE 6.AE 6.RE 6.RE 7E 7E 8E 8E 11E 18E 18.BF 1F 2F 3F 4D 8.AD 9.AD 11.AD 11.RA 1.GE 0.GG.3G.4D 10.GD 11.GD 12.GD 13.GA 8.ILSA 8.IAOD 18D 16D 16D 11.CRD 11.RRD 11.FS 12S 12.CS 10S 10S 13S 13S 11S 11.CS 14S 14S 16S 16S 15.BS 15.DS 15.AS 15.CS 15.ES 18S 18.BS 1S 11.ES 12.ES 10.BS 14.CS 14.LTTS 11.OS 13.O with forced yearly totalsMap cset's not the same lengthMap output string not long enoughAC??ffffff???8OLDmodel file for automatic model selectionmdlinp.f  T78$ERROR: Order of the differencing operator is too large.ERROR: Order of the AR operator is too large.ERROR: Cannot have a seasonal difference with seasonal regression effects.ERROR: Order of the full differencing operator is too large.ERROR: Order of the MA operator is too large.?medabs.f(/,' Work array too small',i6,' <',i6)D@h㈵>(//,' BACKCASTING',/,' Origin',a10,/,' Number',i10)?(/,' ',a)Backcasts and Standard Errors of the Prior Adjusted and Transformed DataBackcasts and Standard Errors of the Transformed DataBackcasts and Standard Errors of the Prior Adjusted DataBackcasts and Standard ErrorsZ(a:,a,a,a,a:,a,a)datebackcaststandarderror------(' ',77(a))-(' ',a,'Standard',/,' ',a,'Date',a,'Backcast',a, 'Error')('(a',i2.2,',f',i2.2,'.',i2.2,',f',i2.2,'.',i2.2,')')xConfidence intervals with coverage probability ((f8.5,')')[On the Original Scale Before Prior AdjustmentsBefore Prior Adjustments After Prior AdjustmentsAfter Prior Adjustments(/, ' WARNING: User-defined prior adjustment factor not provided' ,/,' for the backcast period.',/)(' ',a)with LogNormal correction(' ',a,'Date',a,'Lower',a,'Backcast',a,'Upper')('(a',i2.2,',f',i2.2,'.',i2.2,',2f',i2.2,'.',i2.2,')')lowerciuppercimkback.f easter[easterstock[statcaneaster[]L8^@2ı.n?H?S? lomloqlpyear///@NonseasonalSeasonalPeriod Difference AOLSTCmkotky.f(/,5x,a,1x,'Outlier t-values have been set to zero for ', 'the following observations:')P (a) (also adjusted for (also adjusted for combined trading day trading day prior trading day holiday LS ramp TC AO outlier user-defined effects (adjusted for prior regARIMA irregular regression X-11 Easter factors) (includes seasonal, (includes First pass - Estimating irregular regression and X-11 Easter effectsirregular regression effectsX-11 Easter effects Length of month Length of quarter Leap year (from trading day regression) and prior adjustments.prior adjustments included from Table A2. (Prior, irregular regressionIrregular regression, adjustments applied to A1) (Permanent prior adjustments applied to A1) (regARIMA trading day and holidaytrading dayholiday factors applied to A1) with forced yearly totals (A1 adjusted by C20 whenever C17 = 0) (D11 with D12 trend substituted whenever C17 = 0) (D13 with 0.0 substituted whenever C17 = 0) (D13 with 1.0 substituted whenever C17 = 0) (E2 with D12+(A1-E1) value substituted whenever C17 = 0) (LS outliers included) holiday) (includes leap year regressor) length of month regressor) length of quarter regressor)stock length of month regressor) leap year preadjustment) length of month preadjustment) length of quarter preadjustment) (trading day and holiday) (prior and irregular regression trading day and holiday)AOrampTCspcorispccompspcsaspcindsaspcirrspcindirrspcextrsdspcrsd10*Log(Spectrum_Ori)10*Log(Spectrum_OtlAdjOri)10*Log(Spectrum_AdjOri)10*Log(Spectrum_ModOri)10*Log(Spectrum_Comp)10*Log(Spectrum_OtlAdjComp)10*Log(Spectrum_AdjComp)10*Log(Spectrum_ModComp)10*Log(Spectrum_ExtRsd)10*Log(Spectrum_Rsd)10*Log(Spectrum_IndSA)10*Log(Spectrum_SA_SEATS)10*Log(Spectrum_SA)10*Log(Spectrum_IndIrr)10*Log(Spectrum_Irr_SEATS)10*Log(Spectrum_Irr)10*Log(Spectrum)Spectrum_OriSpectrum_OtlAdjOriSpectrum_AdjOriSpectrum_ModOriSpectrum_CompSpectrum_OtlAdjCompSpectrum_AdjCompSpectrum_ModCompSpectrum_ExtRsdSpectrum_RsdSpectrum_IndSASpectrum_SA_SEATSSpectrum_SASpectrum_IndIrrSpectrum_Irr_SEATSSpectrum_IrrSpectrum Original Series (Table A1) original series (Table A1) Outlier Adjusted Series (Table A19) outlier adjusted series (Table A19) Original Series (Table A1 or A19) original series (Table A1 or A19) Prior Adjusted Series (Table B1) prior adjusted series (Table B1) Original Series (Table A1 or B1) original series (Table A1 or B1) Modified Original Series (Table E1) modified original series (Table E1)mkssky.f(' NT - Observation not included in sliding spans ', 'comparisons.',/)(' SC - A sign change can be found for this ', 'observation.',/)(' IE - The estimates of this effect are ', 'inconsistent for this observation;', /,' one span indicates that the effect causes ', 'an increase in the ', /,' observed value, another that it causes a ', 'decrease.',/)(' TP - Span values for this observation have a ', 'turning point.',/)(' ',i1,a1,' - The maximum percentage difference is ', 'greater than or equal to ',f4.1,'%',/, ' but less than ',f4.1,'%.',/)(' ',i1,a1,' - The maximum percentage difference is ', 'greater than or equal to ',f4.1,'%.',/)(' ')Tukey(Spectrum_Ori)Tukey(Spectrum_OtlAdjOri)Tukey(Spectrum_AdjOri)Tukey(Spectrum_ModOri)Tukey(Spectrum_Comp)Tukey(Spectrum_OtlAdjComp)Tukey(Spectrum_AdjComp)Tukey(Spectrum_ModComp)Tukey(Spectrum_ExtRsd)Tukey(Spectrum_Rsd)Tukey(Spectrum_IndSA)Tukey(Spectrum_SA_SEATS)Tukey(Spectrum_SA)Tukey(Spectrum_IndIrr)Tukey(Spectrum_Irr_SEATS)Tukey(Spectrum_Irr)Tukey(Spectrum) tdtdnolpyeartd1coeftd1nolpyeartdstock1coef[tdstock[///: Direct seasonal adjustment.: Indirect seasonal adjustment.. 8mlist.f(' S 7.',a2,' Sliding spans analysis of ',a,' for ',a,a)(' ')Footnote(' Footnotes for Table S7.',a2,':',/, ' Sliding spans analysis of ',a,' for ',a,a,/).Ai mstest.f(/,a,'Cannot compute moving F-statistic since residual ', 'mean square', /,a,'error is equal to zero for this series.') WARNING: (/,' Moving Seasonality Test'/)(a,'Sum of squares',2x,'Dgrs.freedom',2x,'Mean square',5x, 'F-value',/,a,'Between Years', f17.4,i9,f17.6,f12.3,a2,/,a,'Error',f17.4,i9,f17.6,/)(//,a,'Moving Seasonality Test')(a,'Sum of',5x,'Dgrs.of',9x,'Mean',/,a,'Squares',5x, 'Freedom',8x,'Square',7x,'F-value',/,a,'Between Years', f17.4,i9,f17.6,f12.3,a2,/,a,'Error',f17.4,i9,f17.6,/)(a,A2, 'Moving seasonality present at the one percent level.')(a,A2, 'No evidence of moving seasonality at the five percent level.')(a,'Moving seasonality present at the five percent level.')?Y@?@no(a,'.dom: ',a)mxpeak.f?$@@nmlmdl.f(' NOTE: The SEATS signal extraction routines cannot', ' process more than ',i3,/,' ',a,' terms.',/, ' The program will stop executing; try ', 'specifying another ARIMA model.',/)Nonseasonal AR(' NOTE: The SEATS signal extraction routines cannot', ' process missing lag models.',/, ' The program will stop executing; try ', 'specifying another ARIMA model.',/)Seasonal ARNonseasonal MASeasonal MAnrmtst.f(/,' Number of residuals : ',i5,/)NOTE: The program cannot compute the significance of skewness statistic on less than 25 observations.(' ',a,t26,':',f10.4,t40,a)Skewness coefficient(significant negative skewness at one percent level)(a,':',f10.4,1x,a)skewness- Skewness coefficient (significant negative skewness)(significant positive skewness at one percent level)+ (significant positive skewness) NOTE: The program cannot compute the significance of Geary's a statistic on less than 11 observations. on more than 1001 observations.Geary's a(significant at one percent level)a* Geary's a statistic (significant)NOTE: The program cannot perform hypothesis tests for kurtosis on less than 50 observations.NOTE: The program cannot perform hypothesis tests for kurtosis on more than 1000 observations.Kurtosiskurtosis Kurtosis(/,' Significant skewness has been detected in the ', 'model residuals;', /,' this makes the Geary''s a and Kurtosis statistics ', 'unreliable indicators', /,' of the normality of the residuals.')(/,' A significant value of one of these statistics ', 'indicates that the', /,' standardized residuals do not follow a standard ', 'normal distribution.', /,' If the regARIMA model fits the data well, such lack ', 'of normality', /,' ordinarily causes no problems.',/, /,' However, a significant value can occur because ', 'certain data effects are', /,' not captured well by the model. Sometimes these ', 'effects can be captured', /,' by additional or different regressors (e.g. trading ', 'day, holiday or ',/,' outlier regressors).',/, /,' There are other important effects that can cause a ', 'significant value,', /,' such as random variation of the coefficients or ', 'time-varying conditional', /,' variances, which cannot be represented by regARIMA ', 'models. These other', /,' effects cause the t-tests, AIC''s and forecast ', 'coverage intervals of', /,' ',a,' to have reduced reliability. Their ', 'presence is often', /,' indicated by significant (high) values of the ', 'Ljung-Box Q-statistics of',/,' the squared residuals.')X-13ARIMA-SEATS(/,' No indication of lack of normality.')@S㥛@?Y@olsreg.f(/,' Elements needed for [X:y]''[X:y] =',i3,' *(',i3, ' +1)/2 >',i5).orimvadjcadoadadororicntpriorppriortpriorpadjppradjpadjtppradjtotlaolstcsortdrholusrdefrgseastrancmpidacfidpacfmdlestregrsdfintstacfpacfacf2ftrfctbtrbctsporsprsdspsaspirspcssaspcsirspexrsdindspsaindspircmpsporsptukorsptukrsdsptuksasptukirspctukssaspctuksirsptukexrsdindsptuksaindsptukircmpsptukormorimsamirrsisioxrsisfsfrsfshnksasactrnirrirrwtxtrmxeastrcholcafcalarattadjsatsarfrfcptdxtdctdxholxcalccalahstcsahstindahsttrnhstctrhstsfhstaichstfcthstcfchstarmahsttdhstsfssindsfsschssindchsssassindsassyyssindyysstdsscmporicmppadjadjcoricmpcadcmpoadindsiindrsiindsfindsaindtrnindirrindmoriindmsaindmirrindaratindtadjindsatindsarindlsindaoindcalindcafindfrfcseattrnsettrcseatsfseatirrseatsasetsacsettrnsseataftrnfctdsffctdorifctdsafctdtranfcdsetaratsettadjsgsafsgsacsgtrnfsgtrnctssactstrncfltsaffltsacflttrnfflttrncseatdoriseatdsaseatdtrseatssmseatcycseatlttseatsseseataseseattseseatcseseatsaotlseatirrotl(a,t12,a)UNKNOWN(/, ' FILE SAVE REQUESTS (* indicates file exists and will be overwritten)')(' ',a,a,' ',a)* opnfil.fPoutchr.f(1X,A)('(1X,F10.2,',I3,'A1,F10.2)')(1X,120A1)(1X,10X,110A1)(T20,I4,' TO ',I4)(12X,A)S=SEASONAL FREQUENCIES, T=TRADING DAY FREQUENCIESS=SEASONAL FREQUENCIES(12X,I4,8(8X,I4))(18X,I4,7(8X,I4))(12X,I4,12(4X,I4))@pacf.f(/,' Lag ',12I6)(' PACF',12F6.2)(' SE ',12F6.2)?Trading Day1-Coefficient Trading DayStock Trading Day1-Coefficient Stock Trading DayEasterStatCanEasterStockEasterConstant(5x,'Deleted ',a,' regressor(s) due to insignificant ', 't-value.')trading day?constantpass0.f?pass2.f(' ',a) Model changed to (' ',2(' (',i2,',',i2,',',i2,')'))(' ',2(' (',i2,',',i2,',',i2,')'),a) with constant term without constant term(/,' Confidence coefficient for Ljung-Box Q at lag ',i3, ' = ',f10.4,',' /,' which is greater than the acceptance limit, ',f10.4, '.')(/,' Automatic outlier identification will be redone.',/)(' Critical Value for ',a,' outlier id changed to:',1x, F12.3)AOLSTC(/,' Model changed to ',a, ' due to unacceptable Ljung-Box Q statistics', /,' for previously identified models.')(/,' Model changed to ',a,' due to estimation errors.')ffffff??= ףp=??PERT!@?@?Q?ffffff@pctrit.f(/,2x,a,t50,i3,' out of ',i3,' (',f5.1,' %)')('s2.',a,'.per: ',i3,2x,i3,2x,f7.3)(/,' Percentage of ',a,'s flagged as unstable',a)(2x,a,' : ',t50,i3,' out of ',i3,' (',f5.1,' %)')(///,10x,'Recommended limits for percentages:',/, 10x,'-----------------------------------',//, 5x,a,t55,'35% is too high',/,t55,'40% is much too high',//)(///,10x,'Recommended limits for percentages:',/, 10x,'-----------------------------------',//,5x, a,t55,'15% is too high',/,t55,'25% is much too high',//, 5x,a,t55,'35% is too high',/,t55,'40% is much too high',//)(5x,a,t55,'10% is usually too high',//)(/,5x,'Threshold values used for Maximum Percent ', 'Differences to flag ',a,/,5x,' as unstable',/)monthsquarters(5x,a,t55,'Threshold = ',f5.1,' %')function ABORTAAddPols reach the MaxPol polynomialspolynom.f(A)(A,A)AppendStr: reach MaxStrLength(A,A,A,A) xAppendLine MaxStrLength reached ((A,"^",I1)(A,"^",I2)(A,I2,A)(A,I1,A)(A,"1")("1")("+",G11.4)(G11.4))X@ư>B []=("at at~niid(0,",G11.4,")")]m(t)=(" niid~(0,",G11.4)Va)]C(t)=Bz(t)=ؗҜ ',f6.2,'%')(' Insufficient data to compute the average forecast ', 'error for this model.')(' Insufficient data to compute the Ljung-Box chi-', 'square probability for this model.')(' Ljung-Box Q chi-square probability < ',f6.2,' %')(' Ljung-Box Q chi-square probability < ',e17.10,' %')(' ',a,'vidence of ',a,' overdifferencing',a)Enonseasonal.(/,' MODEL ',i3,' REJECTED: ',/, ' Average backcast error > ',f6.2,'%')WARNING: Eseasonal (see message below).{Gzt?prtchi.f()(/,' Chi-squared Tests for Groups of ',a)(' ',120(a))-(' Regression Effect',t37,'df',t45,'Chi-Square',t61, 'P-Value')(' ',a,t41,'All coefficients fixed')(' ',a,/,t35,i4,f16.2,f13.2)(' ',a,t35,i4,f16.2,f13.2)(' ',a,t52,'Not tested') -prtcol.f(a) ? -('f',i2,'.',i1)('f',i1,'.',i1)n (2x,i4,3x,3(3(@,a):,/,9x),3(@,a),4x,#)(1x,a5,3x,3(3(@,a):,/,9x),3(@,a))(2x,i4,4x,3(@,a):,/,9x,@,a,35x,#)(1x,a5,4x,3(@,a):,/,9x,@,a1)(2x,i4,3x,2(4(@,a):,/,9x),4(@,a),3x,#)(1x,a5,3x,2(4(@,a):,/,9x),4(@,a))(2x,i4,3x,4(@,a),3x,#)(1x,a5,3x,4(@,a))(2x,i4,4x,2(4(5x,@,a):,/,9x),4(5x,@,a),10x,#)(1x,a5,4x,2(4(5x,@,a):,/,9x),4(5x,@,a))(2x,i4,4x,4(5x,@,a),10x,#)(1x,a5,4x,4(5x,@,a))(2x,i4,4x,6(@,a):,/,10x,6(@,a),4x,#)(1x,a5,4x,6(@,a):,/,10x,6(@,a))(2x,i4,4x,6(@,a):,/,10x,6(@,a),4x,#)(1x,a5,4x,6(@,a):,/,10x,6(@,a))(2x,i4,4x,8(@,a):,/,10x,4(@,a),56x,#)(1x,a5,4x,8(@,a):,/,10x,4(@,a))(2x,i4,4x,12(@,a),4x,#)(1x,a5,4x,12(@,a))(2x,i4,3x,5(2(@,a):,/,9x),2(@,a),4x,#)(1x,a5,3x,5(2(@,a):,/,9x),2(@,a)))(2x,i4,3x,2(@,a):,/,9x,2(@,a),4x,#)(1x,a5,3x,2(@,a):,/,9x,2(@,a))('a',i2)('a',i1)(2x,i4,3x,3(3(1x,@):,/,9x),3(1x,@),4x,#)(1x,a5,3x,3(3(1x,@):,/,9x),3(1x,@))(2x,i4,4x,3(1x,@):,/,11x,@,35x,#)(1x,a5,4x,3(1x,@):,/,11x,@)(2x,i4,3x,2(4(1x,@):,/,9x),4(1x,@),3x,#)(1x,a5,3x,2(4(1x,@):,/,9x),4(1x,@))(2x,i4,3x,4(1x,@),3x,#)(1x,a5,3x,4(1x,@))(2x,i4,4x,2(4(6x,@):,/,9x),4(6x,@),10x,#)(1x,a5,4x,2(4(6x,@):,/,9x),4(6x,@))(2x,i4,4x,4(6x,@),10x,#)(1x,a5,4x,4(6x,@))(2x,i4,4x,6(1x,@):,/,10x,6(1x,@),4x,#)(1x,a5,4x,6(1x,@):,/,10x,6(1x,@))(2x,i4,4x,6(1x,@):,/,10x,6(1x,@),4x,#)(1x,a5,4x,6(1x,@):,/,10x,6(1x,@))(2x,i4,4x,8(1x,@):,/,10x,4(1x,@),56x,#)(1x,a5,4x,8(1x,@):,/,10x,4(1x,@))(2x,i4,4x,12(1x,@),4x,#)(1x,a5,4x,12(1x,@))(2x,i4,3x,5(2(1x,@):,/,9x),2(1x,@),4x,#)(1x,a5,3x,5(2(1x,@):,/,9x),2(1x,@)))(2x,i4,3x,2(1x,@):,/,9x,2(1x,@),4x,#)(1x,a5,3x,2(1x,@):,/,9x,2(1x,@)) XXXXX(' ')(/,' No extreme values or regARIMA outliers.')(' Key to symbols:')(/,' Key to symbols:')(' * : extreme value as determined by X-11 extreme', ' value procedure')(' # : regARIMA outlier (either AO, LS, TC, or ', 'Ramp)')(' @ : extreme value and at least one type of ', 'regARIMA outlier')(' & : more than one type of regARIMA outlier')(' - : values around a level shift most likely to be', ' influenced by it'): ('d8b.',i2.2,a,1x,a)c:noneprtd8b.fprtd9a.f('d9a.',i2.2,':',3(1x,E17.10)) ('f',i2,'.3')('f',i1,'.3') (2x,i4,3x,3(3(1x,@):,/,9x),3(1x,@),4x,#)(1x,a5,3x,3(3(1x,@):,/,9x),3(1x,@))(2x,i4,4x,3(1x,@):,/,11x,@,35x,#)(1x,a5,4x,3(1x,@):,/,11x,@)(2x,i4,3x,2(4(1x,@):,/,9x),4(1x,@),3x,#)(1x,a5,3x,2(4(1x,@):,/,9x),4(1x,@))(2x,i4,3x,4(1x,@),3x,#)(1x,a5,3x,4(1x,@))(2x,i4,4x,2(4(6x,@):,/,9x),4(6x,@),10x,#)(1x,a5,4x,2(4(6x,@):,/,9x),4(6x,@))(2x,i4,4x,4(6x,@),10x,#)(1x,a5,4x,4(6x,@))(2x,i4,4x,6(1x,@):,/,10x,6(1x,@),4x,#)(1x,a5,4x,6(1x,@):,/,10x,6(1x,@))(2x,i4,4x,6(1x,@):,/,10x,6(1x,@),4x,#)(1x,a5,4x,6(1x,@):,/,10x,6(1x,@))(2x,i4,4x,8(1x,@):,/,10x,4(1x,@),56x,#)(1x,a5,4x,8(1x,@):,/,10x,4(1x,@))(2x,i4,4x,12(1x,@),4x,#)(1x,a5,4x,12(1x,@))(2x,i4,3x,5(2(1x,@):,/,9x),2(1x,@),4x,#)(1x,a5,3x,5(2(1x,@):,/,9x),2(1x,@)))(2x,i4,3x,2(1x,@):,/,9x,2(1x,@),4x,#)(1x,a5,3x,2(1x,@):,/,9x,2(1x,@)) I S RATIO(//)prtdtb.f(/,' F 4. Multiplicative Trading Day Component Factors:', /,' Day of Week and Leap Year Factors')(/,' F 4. Additive Day of the Week Trading Day Component', ' Factors')8('(1x,a,7(1x,f8.',i1,'))')Irregular Component RegressionregARIMA(//,6x,'Nonseasonal component of length of ',a,' effect ', '("Leap Year" factors):',/)(2x,a15,f7.2,2x,a15)Y@(//,6x,'Nonseasonal component of length of ',a, ' effect ("Leap Year" factors):',/,6x,'before ',a)(//,6x,'Nonseasonal component of length of ',a, ' effect ("Leap Year" factors):',/,6x,'starting ',a)Y@prtdwr.f(1x,a) Regression Trading Day Weights(5x,'(Regression Trading Day Coefficients expressed as ',/, 6x,'X-11 Trading Day Weights)',/)---------------------------------------------------------------(' Mon Tue Wed Thu Fri Sat', ' *Sun (derived)')(8x,7f8.4)(8x,7f8.1)?prterr.f(/,' Error(s) found while estimating the regARIMA model.',/, ' For more details, check the error file (',a,'.err).',/)(/,' ERROR: Nonlinear estimation error with unknown cause ', 'during ',/,' sliding spans analysis.')(/,' ERROR: Nonlinear estimation error with unknown cause ', 'during ',/,' revisions analysis.')(/,' ERROR: Nonlinear estimation error with unknown cause.', /)data(/,' ERROR: Regression matrix singular because of ',a,'.', /,' Remove variable(s) from regression spec and ', 'try again.',/)(/,' ERROR: Regression matrix singular because of ',a,'.', /,' Check regression model or change automatic ', 'outlier options', /,' i.e. method to addone or types to identify AO ', 'only.',/)Regression Matrix(/,' WARNING: Improper input parameters to the likelihood', 'minimization routine.', /,' Please send us the data and spec file that ', 'produced this', /,' message (x12@census.gov).')iterationsfunction evaluations(/,' WARNING: Estimation was terminated because no ', 'further improvement in', /,' the likelihood was possible. Check ', 'iteration output to ', /,' confirm that model estimation really ', 'converged.')(/)(' Convergence tolerance on the likelihood is ', 'too strict.',/)(/,' WARNING: Convergence tolerance for the relative ', 'difference in the', /,' parameter estimates is too strict.')(/,' Cosine of the angle between the vector of ', 'expected values and ', /,' any column of the jacobian is too small.',/)(' This warning occurred during the sliding spans', 'analysis.',/)(' This warning occurred during the history ', 'analysis.',/)(/,' ERROR: ',a,' has roots inside the unit circle but ',/, 'some',/, ' parameters are fixed so cannot invert the ', 'operator.',/)(' This error occurred during the sliding spans ', 'analysis.',/)(' This error occurred during the history ', 'analysis.',/)(/,' ERROR: ',a,' has roots inside the unit circle but ', 'some are missing', /,' so cannot invert the operator. Try ', 'including all lags.',/)(/,' ERROR: Convergence tolerance must be set larger than ', 'machine', /,'precision',e25.14,'.',/)(/,' WARNING: Deviance was less than machine precision ', 'so could not', /,' calculate the relative deviance.',/)(/,' WARNING: The covariance matrix of the ARMA ', 'parameters is singular,', /,' so the standard errors and the correlation ', 'matrix of the ARMA', /,' parameters will not be printed out.',/)(/,' ERROR: Differencing has annihilated the series.',/, ' Check the model specified in the arima spec,', ' set or change',/, ' the possible differencing orders (if using the ', 'automdl spec), or',/, ' change the models specified in the automatic ', 'model file',/, ' (if using the pickmdl spec).')data(' Error(s) found while estimating the irregular ', 'regression model.',/, ' For more details, check the error file (',a,'.err).')(/,' ERROR: Irregular regression matrix singular ', 'because of ',a,'.', /,' Check irregular regression model.',/)Irregular Component Regression Matrixprterx.fprtf2.f(3X,'F 2.A: Average ',a,' without regard to sign over the', /,10x,'indicated span',/,6X,'Span',/,7X,'in',6X,A1,'1',5X, 'D11',5X,'D13',5X,'D12',5X,'D10',6X,'A2',5X,'D18',6X,'F1', /,3X,A7,'s',4X,'O',6X,'CI',7X,'I',7X,'C',7X,'S',7X,'P',5X, 'TD&H',5X,A3)(7X,I2,8F8.2)(/,6X,'Span',/,7X,'in',5X,'E1',6X,'E2',6X,'E3',/,3X,A7,'s', 2X,'Mod.O Mod.CI Mod.I')(7X,I2,3F8.2)(/,3X,'F 2.B: Relative contributions to the variance of the' ,a15,/,10x,'in the components of the original series',/,6x, 'Span',/,7X,'in',5X,'E3',5X,'D12',5X,'D10',6X,'A2',5X, 'D18',12X,'RATIO',/,3X,A7,'s',3X,'I',7X,'C',7X,'S',7X,'P', 5X,'TD&H',4X,'TOTAL (X100)')(7X,I2,5(2PF8.2),' 100.00',2PF8.2)(/,3X, 'F 2.C: Average ',A,' with regard to sign and standard',/, 10x,'deviation over indicated span',/,6X,'Span',8X,A1,'1', 15X,'D13',14X,'D12',/,7X,'in',10X,'O',16X,'I',16X,'C',/, 3X,A7,'s',3(3X,'Avg.',4X,'S.D.',2X))(7X,I2,3(F9.2,F8.2))(/,6X,'Span',8X,'D10',14X,'D11',15X,'F1',/,7X,'in',10X,'S', 16X,'CI',14X,A3,/,3X,A7,'s',3(3X,'Avg.',4X,'S.D.',2X))(/,3X,'F 2.D: Average duration of run',8X,'CI',6X,'I',7X, 'C',6X,A3,/,36X,4F8.2)(//,3X,'F 2.E: I/C Ratio for ',A,'s span')(/,6x,'SPAN ',7I8)(6x,'I/C ',6F8.2)(/,7X,A7,'s for cyclical dominance:',i8)(//,3X,'F 2.F: Relative contribution of the components to ', 'the stationary',/,10x,'portion of the variance in the ', 'original series',//,19x,'I',7x,'C',7X,'S',7X,'P',5X, 'TD&H',3X,'Total',/,14X,6F8.2,/)(/,3X,'F 2.G: The autocorrelation of the irregulars for ', 'spans 1 to',I3)(6x,'ACF ',7f8.2)(/,3X,'F 2.H: The final I/C Ratio from Table D12:',F12.2)(9X,' The final I/S Ratio from Table D10:',F12.2)(/,3X,'F 2.I:',52X,'Statistic Prob.',/,73x,'level',/, 4X,'F-test for stable seasonality from Table B 1.',8x,':', F11.3,F8.2,'%')(4X,'F-test for stable seasonality from Table D 8.',8X,':', F11.3,F8.2,'%',/,4X,'Kruskal-Wallis Chi Squared test',/, 18x,'for stable seasonality from Table D 8. :',F11.3,F8.2, '%',/,4X,'F-test for moving seasonality from Table D 8.', 8X,':',F11.3,F8.2,'%',/)prtf2w.f(6X,'F 2.A: Average ',a, ' without regard to sign over the indicated span',/,14X, 'Span',/,15X,'in',6X,A1,'1',5X,'D11',5X,'D13',5X,'D12',5X, 'D10',6X,'A2',5X,'D18',6X,'F1',13X,'E1',6X,'E2',6X,'E3',/, 11X,A7,'s',4X,'O',6X,'CI',7X,'I',7X,'C',7X,'S',7X,'P',5X, 'TD&H',5X,A3,11X,'Mod.O Mod.CI Mod.I')(15X,I2,8F8.2,9X,3F8.2)(/,6X,'F 2.B: Relative contributions to the variance of the' ,a15,' in the components of the original series',/,14x, 'Span',/,15X,'in',5X,'E3',5X,'D12',5X,'D10',6X,'A2',5X, 'D18',12X,'RATIO',/,11X,A7,'s',3X,'I',7X,'C',7X,'S',7X,'P', 5X,'TD&H',4X,'TOTAL (X100)')(15X,I2,5(2PF8.2),' 100.00',2PF8.2)(/,6X,'F 2.C: Average ',A, ' with regard to sign and standard deviation over indicated span' ,/,14X,'Span',8X,A1,'1',15X,'D13',14X,'D12',14X,'D10',14X,'D11', 15X,'F1',/,15X,'IN',10X,'O',16X,'I',16X,'C',16X,'S',16X,'CI',14X, A3,/,11X,A7,'s',6(3X,'Avg.',4X,'S.D.',2X))(15X,I2,6(F9.2,F8.2))(/,6X,'F 2.D: Average duration of run',8X,'CI',6X,'I',7X, 'C',6X,A3,/,39X,4F8.2)(//,6X,'F 2.E: I/C Ratio for ',A,'s Span',/,18X,12I8)(19X,14F8.2)(/,7X,A7,'s for cyclical dominance:',i8)(//,6X, 'F 2.F: Relative contribution of the components to the stationary portion of the variance in the original series',/,24x,'i',7x,'C', 7X,'S',7X,'P',5X,'TD&H',3X,'Total',/,19X,6F8.2,/)(/,6X, 'F 2.G: The autocorrelation of the irregulars for spans 1 to' ,I3,/,18X,14I8)(/,6X,'F 2.H: The final I/C Ratio from Table D12:',F12.2)(12X,' The final I/S Ratio from Table D10:',F12.2)(/,6X,'F 2.I:',75X,'Statistic Probability',/,100x,'level',/, 13X,'F-test for stable seasonality from Table B 1.',26X, ':',F11.3,F8.2,'%')(13X,'F-test for stable seasonality from Table D 8.',26X, ':',F11.3,F8.2,'%',/,13X, 'Kruskal-Wallis Chi Squared test for stable seasonality from Table D 8. :',F11.3,F8.2,'%',/,13X, 'F-test for moving seasonality from Table D 8.',26X,':',F11.3, F8.2,'%')?YW(//,' FORECASTING',/,' Origin',a10,/,' Number',i10)(/,' ',a)Forecasts and Standard Errors of the Prior Adjusted and Transformed DataForecasts and Standard Errors of the Transformed DataForecasts and Standard Errors of the Prior Adjusted DataForecasts and Standard Errors(a:,a,a,a,a:,a,a)dateforecaststandarderror------('nforctval: ',i3)(' ',77(a))-(' ',a,'Standard',/,' ',a,'Date',a,'Forecast',a, 'Error')('(a',i2.2,',f',i2.2,'.',i2.2,',f',i2.2,'.',i2.2,')')x(' ',a,'Forecast',a,'Standard',/,' ',a,'Date',a,'Data', a,'Forecast',a,'Error',a,'Error',a,'t-value')('(a',i2.2,',f',i2.2,'.',i2.2,',2f',i2.2,'.',i2.2,',f', i2.2,'.',i2.2,',f',i2.2,'.',i2.2,')') ('forctval',i2.2,': ',a,2x,f12.6)Stochastic and regression contributions to the forecast error variances(' ',a,'Regression',a,'Stochastic',a,'Total',a, 'Regression',/,' ',a,'Date',a,'Variance',a,'Variance',a, 'Variance',a,'Percentage')('(a',i2.2,',e',i2.2,'.',i2.2,',2e',i2.2,'.',i2.2,',f', i2.2,'.',i2.2,')')XregressionvariancestochasticvarianceConfidence intervals with coverage probability ((f8.5,')')On the Original Scale Before Prior AdjustmentsBefore Prior Adjustments After Prior AdjustmentsAfter Prior Adjustments(/, ' WARNING: User-defined prior adjustment factor not provided' ,/,' for the forecast period.',/)(' ',a)with LogNormal correction(' ',a,'Date',a,'Lower',a,'Forecast',a,'Upper')('(a',i2.2,',f',i2.2,'.',i2.2,',2f',i2.2,'.',i2.2,')')lowerciupperciprtfct.fprtft.f()(/,' F Tests for ',a,' Regressors',a1) (' ',120(a))-(' Regression Effect',t40,'df',t51,'F-statistic',t66, 'P-Value'):----------------- ------- ----------- ('ftest$',a,': ',2(1x,i4),2(1x,e22.15))(' ',a,t41,'All coefficients fixed')(' ',a,/,t35,i4,',',i4,f16.2,f13.2)(' ',a,t35,i4,',',i4,f16.2,f13.2)(' ',a,t52,'Not tested')prtitr.f(/,' ARMA Iterations')(/,' Iterations',/, ' IGLS: Estimate regression parameters given last values of ARMA parameters.',/, ' ARMA: Estimate ARMA parameters using residuals from last IGLS regression.',/, ' NOTE: ARMA iteration counts are cumulative over IGLS iterations.')(/,' Initial values for the',a) ARMA parameters(' Log Likelihood',1p,e23.9) (1x)(' ','Iteration',t30,i10)IGLS(/,' ',a,' Iteration',t30,i10)(' ',a,' Iteration',t30,i10)(' Function evaluations',t30,i10)(' ',a,' parameters',t25,f15.9,2F18.9,/,(t22,3F18.9))RegressionARMAPERT!@prtlog.f(' Error messages for the input files defined in ',a)(//,' Check ',a,' to see which input files defined ', 'in ',a,/,' were terminated due to errors.')(///,' Input or runtime errors were found in the ', 'following files:')(5x,a,'.spc (Error messages stored in ',a,'.err)')(///,' ',a,' is unable to open input/output files ', 'for the following sets of filenames:')X-13ARIMA-SEATS(2x,i3,2x,'Input filename: ',a,/, 7x,'Output filename: ',a)(2x,i3,2x,'Input filename: NOT SPECIFIED',/, 7x,'Output filename: NOT SPECIFIED')(2x,i3,2x,'Input filename: NOT SPECIFIED',/, 7x,'Output filename: ',a)(2x,i3,2x,'Input filename: ',a,/, 7x,'Output filename: NOT SPECIFIED') ?K (a,e21.14)steplength: ('converged: ',a)yesno(/,' Estimation converged in',i5,' ARMA iterations,',i5, ' function evaluations.')(' Estimation converged in',i5,' ARMA iterations,',i5, ' function evaluations.')(' NOTE: Maximization of the AR(I)MA model likelihood', ' has required more',/, ' than 200 iterations. This could indicate that', ' the model is',/, ' inadequate for the data.')(a,i3)niter: nfev: nreg: (/,' Regression Model')(' ',120(a))-(t30,'Parameter',t47,'Standard',/,' Variable',t31, 'Estimate',t50,'Error',t61,'t-value')(t30,'Parameter',/,' Variable',t34,'Value')('$regression:',/,'$regression$estimates:',/,'group',a, 'variable',a,'estimate',a,'standard error',a, 'fixed',/,'-----',a,'--------',a,'-----------',a, '--------------',a,'-----')(' ',a)change for after@@change for before&&starting(a,a,t25,f14.4,:f16.5,:f13.2)(a,a,t25,f14.4,a16) (fixed)(fixed)(sp,a,a,a,a,e22.15,a,e22.15,a,a)(sp,a,a,a,3(a,e22.15),a,a)$: Trading DayStock Trading DaySun(before(change for beforeSun I(starting(change for afterSun II1-Coefficient Trading Day1-Coefficient Stock Trading DaySat/SunSat/Sun ISat/Sun IISeasonalDecDec IDec IIth I II** * (derived)('nregderived: ',i3)(sp,a,3(a,e22.15),a,a) seasonaltrigonometric seasonaltrading daylength-of-monthlength-of-quarterleap yearstock trading daystock length-of-monthregression()(' &The I values estimate the ',a,' coefficients', /,' for the span of data before the change date.')(' &&The I values estimate how much the early ',a, /,' coefficients differ from those estimated for the span', ' of data',/,' starting at the change date.')(' @The II values estimate the ',a,' coefficients', /,' for the span of data starting at the change date.')(' @@The II values estimate how much the early ',a, /,' coefficients differ from those estimated for the span', ' of data',/,' before the change date.')(' *For full trading-day and stable seasonal effects, ', 'the derived',/, ' parameter estimate is obtained indirectly as minus ', 'the sum',/, ' of the directly estimated parameters that define the ', 'effect.')(' **For the one coefficient trading-day effect, the ', 'derived',/, ' parameter estimate is obtained indirectly as minus ', '-2.5 times',/, ' the directly estimated parameter that defines ', 'the effect.')chi$Regressorsnonseasonaldiff: seasonaldiff: nmodel: (' ',a,': ',a)(' ',a,':',t28,i2)Nonseasonal differencesSeasonal differences(t47,'Standard',/,' Parameter',t31,'Estimate',t49, 'Errors')(/,' Parameter',t26,'Value (fixed)')(/,' Parameter',t34,'Value')('$arima:',/,'$arima$estimates:',/,'operator',a,'factor', a,'period',a,'lag',a,'estimate',a,'standard error',a, 'fixed',/,'--------',a,'------',a,'------',a,'---',a, '--------',a,'--------------',a,'-----')('$arima:',/,'$arima$estimates:',/,'operator',a,'factor', a,'period',a,'lag',a,'estimate',a,'fixed',/,'--------', a,'------',a,'------',a,'---',a,'--------',a,'-----')(' ',a,t45,a)(' ',a,' ',a)(' Lag',i3,f29.4,' ',a)(' Lag',i3,' ',a,t19,f20.4)(a,a,a,a,i2.2,a,i2.2,a,sp,e21.14,a,a)(a,a,a,a,i2.2,a,i2.2,a,sp,3(e21.14,a),a)(a,a,a,a,i2.2,a,i2.2,a,sp,e21.14,a,e21.14,a,a)(a,e33.5) Variance SE of Var(sp,'$variance:',//,'mle',a,e21.14,/,'se',a,e21.14)('$modelspan: ',a,' to ',a)(1x,a)-----variance$mle: variance$se: (' Lag',i3,f29.4,f16.5)prtmdl.fprtmsp.f(a,': ',a,' to ',a) Irregular Component Regression Span regARIMA Model Span(/,a,/,' From ',a,' to ',a) -&X-11 Easter adjustment factorscombined holiday componentcombined adjustment factorscombined adjustment factors (saved as percentages if multiplicative adj)final adjustment differencescombined calendar adjustment factorsfinal adjustment ratiostotal adjustment factorsoriginal series adjusted by preliminary irregular regression factorsoriginal series adjusted by final irregular regression factorssummary measuresmonitoring and quality assessment statistics^ of annual totalsF-tests for seasonalityMoving seasonality ratiofinal seasonal filter selection via GLOBAL MSRoriginal series,@-seasonally adjusted series,coincidence of points^ of the original series modified for extremes^ of the S. A. series modified for extremesfinal seasonal factors with one year forecastsfinal seasonally adjusted seriesfinal trend cyclefinal irregular componentforecasts of final seasonally adjusted seriesforecasts of final trend cycleforecasts of final irregular weightsfinal seasonally adjusted series with forced yearly totalsrounded final seasonally adjusted series% in seasonally adjusted series with forced yearly totals (D11.A)% in seasonally adjusted series with forced yearly totals (D11.A - saved as percentages if appropriate)% in rounded seasonally adjusted series (D11.R)% in rounded seasonally adjusted series (D11.R - saved as percentages if appropriate)factors applied to adjusted series to get adjusted series with forced yearly totalsratios or differences in annual totals and indirect seasonally adjusted seriesfactors applied to get adjusted series with forced yearly totals(a) Year('a',i2)('a',i1)(2x,i4,3x,3(3(1x,@):,/,9x),3(1x,@),4x,#)(1x,a5,3x,3(3(1x,@):,/,9x),3(1x,@))(2x,i4,4x,3(1x,@):,/,11x,@,35x,#)(1x,a5,4x,3(1x,@):,/,11x,@)(2x,i4,3x,2(4(1x,@):,/,9x),4(1x,@),3x,#)(1x,a5,3x,2(4(1x,@):,/,9x),4(1x,@))(2x,i4,3x,4(1x,@),3x,#)(1x,a5,3x,4(1x,@))(2x,i4,4x,2(4(6x,@):,/,9x),4(6x,@),10x,#)(1x,a5,4x,2(4(6x,@):,/,9x),4(6x,@))(2x,i4,4x,4(6x,@),10x,#)(1x,a5,4x,4(6x,@))(2x,i4,4x,6(1x,@):,/,10x,6(1x,@),4x,#)(1x,a5,4x,6(1x,@):,/,10x,6(1x,@))(2x,i4,4x,6(1x,@):,/,10x,6(1x,@),4x,#)(1x,a5,4x,6(1x,@):,/,10x,6(1x,@))(2x,i4,4x,8(1x,@):,/,10x,4(1x,@),56x,#)(1x,a5,4x,8(1x,@):,/,10x,4(1x,@))(2x,i4,4x,12(1x,@),4x,#)(1x,a5,4x,12(1x,@))(2x,i4,3x,5(2(1x,@):,/,9x),2(1x,@),4x,#)(1x,a5,3x,5(2(1x,@):,/,9x),2(1x,@)))(2x,i4,3x,2(1x,@):,/,9x,2(1x,@),4x,#)(1x,a5,3x,2(1x,@):,/,9x,2(1x,@))(a:,a,a:,a,a)datesf-------prtmsr.f prtmtx.f('(',a,',',i2,'a)')at11 Date ----('(2x,a8,(:t11,',i1,'E',i2,'.4))') log(y/(1-y))Automatic selectionLog(y)?No transformation?sqrt(y)prtnfn.f(f5.2,'^2+((y^',f5.2,')-1)/',f5.2)(f5.2,'^2+((y^',f5.2,')-1)/(',f5.2,')')(a,': ',a) Transformation (' Transformation',/,' ',a)transformaictransExact ARMAExact MA, conditional ARConditionalestimationevaluationevaluation with GLS regression estimatesprtopt.f(' ',a,' likelihood ',a)(' Max total ARMA iterations ',t39,i8)(' Max ARMA iter''s w/in an IGLS iteration ',t39,i8)(' Convergence tolerance ',t38,1p,g9.2)(' ARMA convergence tolerance',t38,1p,g9.2)Y@ SeasonalTrading DayLength-of-MonthLength-of-QuarterLeap YearHolidayAOLS and RampTCUser-definedMissing ValueSOConstantTotal RegReg Resids?DResiduals from the Estimated Regression EffectsDataF& $)*+./0 %!"#  12345 6-,'(7 *,245688prtrev.f('r',i2.2,'.aarmode: ',a)percentdifference('(1x,a5,1x,',i1,'(1x,f9.2))')('(2x,i4,1x,',i1,'(1x,f9.2))') later-Conc - later Final T01revisions history analysisrevision history of the outliers identifiedrevision history of the Moving Seasonality Ratiopercent revisions of the concurrent seasonal adjustmentssummary statistics : average absolute percent revisions of the seasonal adjustmentsconcurrent and revised seasonal adjustments and revisionspercent revisions of the % of the adjustmentssummary statistics : average absolute revisions of the % of the adjustmentshistory of the % of the adjustmentspercent revisions of the concurrent indirect seasonal adjustmentssummary statistics : average absolute percent revisions of the concurrent indirect seasonal adjustmentsconcurrent and revised indirect seasonal adjustments and revisionspercent revision of the concurrent Henderson trend-cycle valuessummary statistics : average absolute percent revision of the concurrent Henderson trend-cycleconcurrent and revised Henderson trend-cycle values and revisionspercent revisions of the % of the trend-cycle valuessummary statistics : average absolute percent revisions of the % of the trend-cyclehistory of the % of the trend-cycle valuesrevisions of the concurrent and projected seasonal componentsummary statistics : average absolute percent revisions of the concurrent and projected seasonal componentconcurrent and projected seasonal component and their percent revisionsrevision history of the likelihood statisticsrevision history of the out-of-sample forecastsforecast and forecast error historySEATS ARIMA model historyseasonal forecast historyARMA model coefficient historytrading day coefficient historysliding spans of the seasonal factorssliding spans of the indirect seasonal factorssliding spans of the changes in the seasonally adjusted seriessliding spans of the changes in the indirect seasonally adjusted seriessliding spans of the seasonally adjusted seriessliding spans of the indirect seasonally adjusted seriessliding spans of the year-to-year changes in the seasonally adjusted seriessliding spans of the year-to-year changes in the indirect seasonally adjusted seriessliding spans of the trading day factors Months: Quarters: Years: Total: Hinge Values: Seasonal Adj.Changes in Adj.Ind. Seasonal Adj.TrendChanges in Trend(' AveAbsRev of ',a,' : ',t40,f10.3)d2y1ylag00('lag',i2.2)('r0',i1,'.',a,'.',a,': ',E17.10)aar.all8('aar.',a,i2.2)p('r0',i1,'.',a,'.',a,': ',a,' ',E17.10)y('r0',i1,'.',a,'.',a,': ',i4,' ',E17.10)hinge.minhinge.25phinge.medhinge.75phinge.max('(1x,a5,1x,2(1x,f',i2,'.',i1,'),1x,f',i2,'.2)')('(2x,i4,1x,2(1x,f',i2,'.',i1,'),1x,f',i2,'.2)')RevisionFinal laterConcurrentSA_revisionCHNG_revisionInd_SA_revisionTRND_revisionCHNG_TRND_revisionSF_revision(1yr-2yr)()(1000a)date---------------------------_SA_CHNG_Ind_SA_TRND_CHNG_TRNDConc(0Conc(Concprtrts.f(/,' Roots of ',a,/,' Root',t25,'Real',t31,'Imaginary', t44,'Modulus',t53,'Frequency',/,a)C('Operator',a,'Factor',a,'Root',a,'Real',a,'Imaginary',a, 'Modulus',a,'Frequency',/,'--------',a,'------',a, '----',a,'----',a,'---------',a,'-------',a,'---------')(' ',a,t35)(' Root',i3,t18,4F11.4)(a,a,a,a,i2.2,a,a)(a)prtrv2.f('r06.aarmode: ',a)percentdifference('(1x,a5,1x,',i1,'(1x,f9.2))')('(2x,i4,1x,',i1,'(1x,f9.2))')Proj -Conc -Final 1revisions history analysisrevision history of the outliers identifiedrevision history of the Moving Seasonality Ratiopercent revisions of the concurrent seasonal adjustmentssummary statistics : average absolute percent revisions of the seasonal adjustmentsconcurrent and revised seasonal adjustments and revisionspercent revisions of the % of the adjustmentssummary statistics : average absolute revisions of the % of the adjustmentshistory of the % of the adjustmentspercent revisions of the concurrent indirect seasonal adjustmentssummary statistics : average absolute percent revisions of the concurrent indirect seasonal adjustmentsconcurrent and revised indirect seasonal adjustments and revisionspercent revision of the concurrent Henderson trend-cycle valuessummary statistics : average absolute percent revision of the concurrent Henderson trend-cycleconcurrent and revised Henderson trend-cycle values and revisionspercent revisions of the % of the trend-cycle valuessummary statistics : average absolute percent revisions of the % of the trend-cyclehistory of the % of the trend-cycle valuesrevisions of the concurrent and projected seasonal componentsummary statistics : average absolute percent revisions of the concurrent and projected seasonal componentconcurrent and projected seasonal component and their percent revisionsrevision history of the likelihood statisticsrevision history of the out-of-sample forecastsforecast and forecast error historySEATS ARIMA model historyseasonal forecast historyARMA model coefficient historytrading day coefficient historysliding spans of the seasonal factorssliding spans of the indirect seasonal factorssliding spans of the changes in the seasonally adjusted seriessliding spans of the changes in the indirect seasonally adjusted seriessliding spans of the seasonally adjusted seriessliding spans of the indirect seasonally adjusted seriessliding spans of the year-to-year changes in the seasonally adjusted seriessliding spans of the year-to-year changes in the indirect seasonally adjusted seriessliding spans of the trading day factors Months: Quarters: Years: Total: Hinge Values: (' AveAbsRev of ',a,' : ',t40,f10.3)SeasonalProjected Seasonal(a,': ',E17.10)r06.lag00.aar.all8('aar.',a,i2.2)p(a,a,': ',a,' ',E17.10)r06.lag00.y(a,a,': ',i4,' ',E17.10)r06.lag00.hinge.minr06.lag00.hinge.25pr06.lag00.hinge.medr06.lag00.hinge.75pr06.lag00.hinge.maxr06.proj.aar.allr06.proj.r06.proj.hinge.minr06.proj.hinge.25pr06.proj.hinge.medr06.proj.hinge.75pr06.proj.hinge.max('(1x,a5,1x,2(2(1x,f',i2,'.1),1x,f',i2,'.2))')('(2x,i4,1x,2(2(1x,f',i2,'.1),1x,f',i2,'.2))')RevisionFinalProjConcPROJ_SF_revisionSF_revision(1000a)date---------------------------Final_SFProj_SFConc_SFprtsft.f()(/,' F Tests for Seasonal Regressors',a1) (' ',120(a))-(' Regression Effect',t40,'df',t51,'F-statistic',t66, 'P-Value'):----------------- ------- ----------- ('sftest$',a,': ',2(1x,i4),2(1x,e22.15))(' ',a,t41,'All coefficients fixed')(' ',a,/,t35,i4,',',i4,f16.2,f13.2)(' ',a,t35,i4,',',i4,f16.2,f13.2)(' ',a,t52,'Not tested')prtshd.f(/,' ',a)(' From ',a,a,' to ',a,/,' Observations ',i6)prttbl.f(/,' ',a)?YearYrValue(200(a)) - (a,a,a,a,4(a,a,a,a))('((i',i2.2,',f',i2.2,'.',i2.2,',:',i2,'(i',i2.2,',f',i2.2, '.',i2.2,')))')('(a,a,a,',i2.2,'(a,a))')('(a,a,a,a,',i2.2,'(a,a))')(a,a,i3,4(a,i3))(a,a,a,i3,4(a,i3))(a,a,a,a,3(a,a))(a,a,a,i3,5(a,i3))('(i',i2.2,',',i1,'(/),',i2,'x,',i2,'f',i2.2,'.',i2.2, ':,/,(',i2,'x,:',i2,'f',i2.2,'.',i2.2,'))')('(i',i2.2,',',i3,'x,:',i2,'f',i2.2,'.',i2.2,',/,(',i2, 'x,:',i2,'f',i2.2,'.',i2.2,'))')('(i',i2.2,',f',i2.2,'.',i2.2,',:',i2,'f',i2.2,'.',i2.2, ' ,/,(',i2,'x,:',i2,'f',i2.2,'.',i2.2,'))')()?{Gz?prttd.f(//,6x,'Day of Week Component for ',a,' Trading Day ', 'Factors (before ',a,'):',/)(//,6x,'Day of Week Component for ',a,' Trading Day ', 'Factors (starting ',a,'):',/)(//,6x,'Day of Week Component for ',a,' Trading Day ', 'Factors:',/)(39x,a,'s starting on:',/,21x,'Mon Tue Wed', ' Thu Fri Sat Sun')prttrn.f('f',i2,'.',i1)('f',i1,'.',i1)n (2x,i4,3x,3(3(@,a):,/,9x),3(@,a),4x,#)(1x,a5,3x,3(3(@,a):,/,9x),3(@,a))(2x,i4,4x,3(@,a):,/,9x,@,a,35x,#)(1x,a5,4x,3(@,a):,/,9x,@,a1)(2x,i4,3x,2(4(@,a):,/,9x),4(@,a),3x,#)(1x,a5,3x,2(4(@,a):,/,9x),4(@,a))(2x,i4,3x,4(@,a),3x,#)(1x,a5,3x,4(@,a))(2x,i4,4x,2(4(5x,@,a):,/,9x),4(5x,@,a),10x,#)(1x,a5,4x,2(4(5x,@,a):,/,9x),4(5x,@,a))(2x,i4,4x,4(5x,@,a),10x,#)(1x,a5,4x,4(5x,@,a))(2x,i4,4x,6(@,a):,/,10x,6(@,a),4x,#)(1x,a5,4x,6(@,a):,/,10x,6(@,a))(2x,i4,4x,6(@,a):,/,10x,6(@,a),4x,#)(1x,a5,4x,6(@,a):,/,10x,6(@,a))(2x,i4,4x,8(@,a):,/,10x,4(@,a),56x,#)(1x,a5,4x,8(@,a):,/,10x,4(@,a))(2x,i4,4x,12(@,a),4x,#)(1x,a5,4x,12(@,a))(2x,i4,3x,5(2(@,a):,/,9x),2(@,a),4x,#)(1x,a5,3x,5(2(@,a):,/,9x),2(@,a)))(2x,i4,3x,2(@,a):,/,9x,2(@,a),4x,#)(1x,a5,3x,2(@,a):,/,9x,2(@,a))('a',i2)('a',i1)(2x,i4,3x,3(3(1x,@):,/,9x),3(1x,@),4x,#)(1x,a5,3x,3(3(1x,@):,/,9x),3(1x,@))(2x,i4,4x,3(1x,@):,/,11x,@,35x,#)(1x,a5,4x,3(1x,@):,/,11x,@)(2x,i4,3x,2(4(1x,@):,/,9x),4(1x,@),3x,#)(1x,a5,3x,2(4(1x,@):,/,9x),4(1x,@))(2x,i4,3x,4(1x,@),3x,#)(1x,a5,3x,4(1x,@))(2x,i4,4x,2(4(6x,@):,/,9x),4(6x,@),10x,#)(1x,a5,4x,2(4(6x,@):,/,9x),4(6x,@))(2x,i4,4x,4(6x,@),10x,#)(1x,a5,4x,4(6x,@))(2x,i4,4x,6(1x,@):,/,10x,6(1x,@),4x,#)(1x,a5,4x,6(1x,@):,/,10x,6(1x,@))(2x,i4,4x,6(1x,@):,/,10x,6(1x,@),4x,#)(1x,a5,4x,6(1x,@):,/,10x,6(1x,@))(2x,i4,4x,8(1x,@):,/,10x,4(1x,@),56x,#)(1x,a5,4x,8(1x,@):,/,10x,4(1x,@))(2x,i4,4x,12(1x,@),4x,#)(1x,a5,4x,12(1x,@))(2x,i4,3x,5(2(1x,@):,/,9x),2(1x,@),4x,#)(1x,a5,3x,5(2(1x,@):,/,9x),2(1x,@)))(2x,i4,3x,2(1x,@):,/,9x,2(1x,@),4x,#)(1x,a5,3x,2(1x,@):,/,9x,2(1x,@))TOTALXXXXX(' ')AVGE (//,' * - Trend cycle estimate that had a negative', ' value replaced by ',a,'.')X-13ARIMA-SEATS(//,' * - Trend cycle estimate that had a negative ', 'value replaced by',/,' ',a,'.')prtukp.f(/,a) Peak probabilities for Tukey spectrum estimator: Indirect adjustments Peak probabilities for Tukey spectrum estimator(' Spectrum estimated from ',a,' to ',a,'.',/)(40x, ' S1 S2 S3 S4 S5 S6 TD', /,40x, '------ ------ ------ ------ ------ ------ ------')  Model Residuals Seasonally adjusted series (E2) Indirect Seasonally adjusted series Seasonally adjusted series (SEATS) Modified Irregular (E3) Indirect Irregular Stochastic Irregular (SEATS)*** (1x,A36,3x,7(3x,a2,4x))(1x,A36,3x,7(F6.3,A2,1x))(' ----------',/, 5x,'** - Peak Probability > 0.99,',/, 5x,' * - 0.90 < Peak Probability < 0.99',//)Gz? prtxrg.f(' Estimation converged in',i5,' ARMA iterations,',i5, ' function evaluations.')(a,i3)nxreg: (/,' Regression Model')(' ',120(a))-(t30,'Parameter',t47,'Standard',/,' Variable',t31, 'Estimate',t50,'Error',t61,'t-value')(t30,'Parameter',/,' Variable',t34,'Value')('$regression:',/,'$regression$estimates:',/,'group',a, 'variable',a,'estimate',a,'standard error',/,'-----',a, '--------',a,'-----------',a,'--------------')()(' ',a)change for after@@change for before&&starting(a,a,t25,f14.4,:f16.5,:f13.2)(a,a,t25,f14.4,a16) (fixed)(fixed)(sp,a,a,a,a,e22.15,a,e22.15,a,a)(sp,a,a,a,3(a,e22.15),a,a)$: Trading DayStock Trading DaySun(before(change for beforeSun I(starting(change for afterSun IISat/SunSat/Sun ISat/Sun II** * (derived)('nxregderived: ',i3)(sp,a,3(a,e22.15),a,a) seasonaltrigonometric seasonaltrading daylength-of-monthlength-of-quarterleap yearstock trading daystock length-of-monthregression(' &The I values estimate the ',a,' coefficients', /,' for the span of data before the change date.')(' &&The I values estimate how much the early ',a, /,' coefficients differ from those estimated for the span', ' of data',/,' starting at the change date.')(' @The II values estimate the ',a,' coefficients', /,' for the span of data starting at the change date.')(' @@The II values estimate how much the early ',a, /,' coefficients differ from those estimated for the span', ' of data',/,' before the change date.')(' *For full trading-day effects, the derived ', 'parameter estimate',/, ' is obtained indirectly as minus the sum of the', ' directly estimated',/, ' parameters that define the effect.')(' **For the one coefficient trading-day effect, the ', 'derived',/, ' parameter estimate is obtained indirectly as minus ', '-2.5 times',/, ' the directly estimated parameter that defines ', 'the effect.')chi$?Regressors(/, ' Variance',e33.5)(sp,'$variance:',/,'ols',a,e21.14)('$x11regression$span: ',a,' to ',a)(1x,a)-----@Y@Can't push input buffer back anymore"" is not the last character Y@COMMENT must be shorter than characters.qcontr.f(/,2X,A7,2X,A6,' -------- -------- ',A40,2x,A8)(36X,A)eEdD^UVwJ?NAME must be shorter than characters.Quote can't wrap to next line--end-of-line assumed to be end qu oteQUOTE must be shorter than characters.Quotes must contain at least one character.@??{Gz?@@4@u?j/ aolstcrpmvtlsoqiqdOutlier type, "" is not an AO, LS, RP, SO, TL, TC, MV, QI or QD.Outlier "" does not occur on a valid date."" is an invalid ramp outlier." is an invalid quadratic ramp outlier." is an invalid temporary level shift outlier.Ramp outlier "" does not have a valid end date.Quadratic Ramp outlier "TL outlier " aoslssOutlier sequence type, "" is not an AOS or LSS.Outlier "" does not occur on a valid date."" is an invalid AO sequence variable." is an invalid level shift sequence variable.AO sequence variable "" does not have a valid end date.LS sequence variable "(starting (before (change from before 4@MbP?$@8H AutoOutlierOutlierregvar.f(/,' Too many elements in [X:y]',i4,' *',i3,' >',i6)B[AOSLSSAOLSRpMiTCSOTLQIQD?span of datauser-defined regression variablesforecastsUser-defined SeasonalUser-defined HolidayUser-defined Holiday Group 2User-defined Holiday Group 3User-defined Holiday Group 4User-defined Holiday Group 5(before (change for before (starting (change for after Trading DayZZ{ZZ ZZZZVZZiZ5ZZZZZ0Z0ZbZcZcZcZcZcZcZcZcZiZZiZ\Z\Z\Z\Z\Z\Z\Z\ZbZZZ ZcZ\ZZ0ZVZcZ\ZbZbZbZbZbZZZbZ\Z{ZZ ZZZZVZZUZ{ZZ ZZZZVZZregx11.f(/,' ERROR: Work array too small,',i4,'*',i4,'>',i6,'.')YK PERT!@?@??Month QuarterLength-of- I IIresid.f(/,' Column error, 1<=begcol<=endcol<= nc',/,26x,3I8)?QPK T7WARNING: History analysis for estimates derived from SEATS adjustments cannot be done when SEATS cannot perform a signal extraction.ERROR: Cannot calculate revision statistics for seasonally adjusted data if seasonal adjustment is not specified via x11 or seats spec.ERROR: Cannot calculate revision statistics for seasonal factorsERROR: Cannot calculate revision statistics for changes in the adjusted dataERROR: Cannot calculate revision statistics for trend componentERROR: Cannot calculate revision statistics for changes in the trend if seasonal adjustment is not performed during SEATS analysis. if trend component not estimated during SEATS analysis.ERROR: Cannot calculate revision statistics for likelihood statistics if regARIMA modelling is not specified.ERROR: Cannot calculate revision statistics for forecasts if no forecasts are specified.ERROR: Cannot calculate revision statistics for ARMA parameters if no ARIMA model is specified.ERROR: Cannot calculate revision statistics for trading day coefficients if no ARIMA model is specified.WARNING: Cannot calculate revision statistics for projected seasonal factors unless either zero forecasts or at least one year of forecasts are specified.ERROR: Cannot calculate revision statistics for ARMA parameters if all coefficients in regARIMA model is fixed (fixmdl=yes). the ARIMA model coefficients are fixed. coefficients if no trading day regressors are specified. coefficients if fixreg=td. coefficients if regARIMA model is fixed (fixmdl=yes). coefficients if all trading day regressors are fixed. are specified via the forecast spec.WARNING: Cannot utilize forecast lead for history that is greater than the number of forecasts (maxlead). History analysis for forecasts will not be done for this run. if a summary measures run is specified in the x11 spec. if a trend estimation run is specified in the x11 spec.(/,' NOTE: Composite seasonal adjustment performed with ', i3,' component(s), ', /,' but the indirect concurrent seasonal ', /,' adjustments collected for', /,' the revisions history analysis were updated ', 'for only ',i3,' component(s).',/, /,' Revisions histories of the indirect ', 'seasonal adjustments will not', /,' be produced. Check for errors in the ', 'revisions histories of the', /,' components, and ensure that a history spec', ' is present in the', /,' spec files of all the components.')(' NOTE: The default starting date of the ',a,' history ', 'analysis has been',/, ' used since it is later than the default starting ', 'date determined by',/, ' the length of the maximum seasonal filter from ', 'the seasonal adjustment.')forecastAICARMA coefficientsTD coefficients(' NOTE: The default starting date determined by the ', 'length of the maximum',/, ' seasonal filter from the seasonal adjustment was ', 'used since it is',/, ' later than the default starting date for the ',a, ' history analysis.')WARNING: Ending date of revisions valid only for estimates derived from seasonal adjustment (seasonally adjusted data, seasonal factors trends, etc.). Ending date of history analysis reset to end of series.NOTE: The start of the history analysis has been advanced to to allow observations between the start of the model span and the start of the history analysis. Due to this change, the program will not generate a history analysis of the indirect seasonal adjustments. Change the starting date for all history analysis to be or later.ERROR: There must be at least observations between the start of the model span and the start of the history analysis when a ARIMA model is present.NOTE: regARIMA model span will be reset during the history analysis.<NOTE: Since the number of observations modeled is less than , regARIMA model span will be reset and regARIMA model parameters will be held fixed during the history analysis. regARIMA model parameters will be held fixed during the history analysis.NOTE: regARIMA model parameters will not be re-estimated once a year during the history analysis.NOTE: In order to allow parameter estimation to occur only once a year, the refresh option is ignored. years between the start of the data span and the start of the history analysis.NOTE: There must be at least years between the start of the data span and the start of the history analysis when seasonal adjustment is performed. History analysis of seasonal adjustments, trends, and their related changes are not performed. years between the start of the data span and the start of the history analysis when seasonal adjustment is performed.WARNING: The start of the history analysis has been changed to to allow observations between the start of the irregular regression and the start of the history analysis. Due to this change, the program will not generate a history analysis of the indirect seasonal adjustments. Change the starting date for all history analysis to be or later.NOTE: Span for irregular regression will be reset.NOTE: Span for irregular regression will be reset and the irregular regression coefficients will be held fixed during the history analysis.NOTE: Irregular component regression parameters will not be re-estimated once a year during the revisions history analysis.NOTE: Not enough data to perform history analysis starting in .NOTE: Not enough data to perform history analysis using default starting date; use start argument in history spec to override default. See Section 7 of the X-13ARIMA-SEATS Reference Manual.(/,' NOTE: Not enough data to perform forecast history ', 'analysis for lag ',i2,/,' starting in ',a,'.', /,' See ',a,' of the ',a,' ',a,'.')Section 7X-13ARIMA-SEATSReference Manual(/,' NOTE: Not enough data to perform forecast history ', 'analysis for lag ',i2,/, ' from default starting date.',/, /,' See ',a,' of the ',a,' ',a,'.')(/,' NOTE: Not enough data to perform a history ', 'analysis for ',a,/, ' at lag ',i2,' starting in ',a,'.',/, /,' See ',a,' of the ',a,' ',a,'.')seasonal adjustments(/,' NOTE: Not enough data to perform a history ', 'analysis for ',a,/, ' at lag ',i2,' from default starting date.', /,' See ',a,' of the ',a,' ',a,'.')trendsWARNING: History analysis will not be performed for this run because of error(s) indicated above. revchk.frevdrv.fERROR: Cannot calculate revision statistics for seasonally adjusted data if a trend estimation run is specified in the x11 spec and trading day and/or holiday factors are held fixed.ERROR: Cannot calculate revision statistics for changs in the adjusted data(starting NOTE: The following change of regime regression variables are not defined for at least one year before the startup period of the history analysis: The regressors listed above will be fixed to their estimated values from the original series.PTrading Day4(/,'ERROR: X-11 Easter adjustment cannot be estimated ', 'for the history', /,' analysis specified in this run',a,/) because there are:.(8x,'No years of data with Easter before April 1st.')(8x,'No years of data with Easter after April 16th.')(8x,'No years of data with Easter between April 2nd ', 'and April 8th.')(8x,'No years of data with Easter between April 8th ', 'and April 15th.')(/,8x,'Either choose a later starting date for the ', 'history analysis', /,8x,'or preadjust the series using Easter ', 'effects estimated from a', /,8x,'regARIMA model.')(/,' No ',a,' kept or deleted during this history ', 'analysis.')outliersNOTE: The user defined regressors listed below were held fixed for at least one span during the history analysis:(/,' NOTE: The seasonal filter used to generate the ', 'seasonal component has ', /,' changed during the revision period. This ', 'could increase the size', /,' of revisions.')('historyindsa: ',a)yesno(a:,a,a:,a,a,a,a)dateLog_LikelihoodAICC-----------------------------(' R 7. Likelihood statistics from estimating ', 'regARIMA model over spans with',/, ' ending dates ',i2,':',i4,' to ',i2,':',i4,//)(3x,'Span End',9x,'Log Likelihood',15x,'AICC',/, 3x,'--------',9x,'--------------',15x,'----')(3x,a,5x,2(3x,f15.3))7SEATS_Model(' R 9. SEATS ARIMA model used for spans with',/, ' ending dates ',i2,':',i4,' to ',i2,':',i4,//)(3x,'Span End',9x,'ARIMA Model',/, 3x,'--------',9x,'-----------')(3x,a,5x,a)no modelnone('(',i2,'a)')('(2x,A,',i2,'(3x,a25))')('(2x,A,',i2,'(10x,f18.6))')- (' R 9.A ARIMA model coefficients used for spans with',/, ' ending dates ',i2,':',i4,' to ',i2,':',i4,//)Span End--------(' R 9.B regARIMA trading day coefficients used for ', 'spans with',/, ' ending dates ',i2,':',i4,' to ',i2,':',i4,/)(/,5x,'Group ',i2,' : ',a,/)('(2x,A,',i2,'(3x,a17))')('(2x,A,',i2,'( 5x,f15.6))')WARNING: History analysis will not be performed for this run because of error(s) indicated above.revhdr.f(//,' R 0 Summary of options selected for revisions ', 'history analysis.', //,' History analysis performed for the following:',/, ' ---------------------------------------------')(5x,'- ',a)Direct and Indirect Seasonally Adjusted SeriesDirect Seasonally Adjusted SeriesFinal Seasonally Adjusted SeriesChanges in Final Seasonally Adjusted SeriesFinal Trend-Cycle ComponentChanges in Final Trend Cycle ComponentAICForecast ErrorsARMA Model CoefficientsTrading Day Coefficients(' ')(' History analysis was not performed on the ', 'Indirect Seasonally Adjusted Series ',/ ' for one of the following reasons:')Identical starting dates not provided for the history analysis of all(7x,a)the components;History analysis of seasonal adjustments not specified for all thecomponents;Starting date specified for total series doesn't match starting date forthe component series;Starting date not specified for total series.(' Revise the input specification files for the ', 'components and total series',/, ' accordingly and rerun the metafile to generate ', 'revisions history analysis for',/ ' the indirect seasonally adjusted series.')Seasonally Adjusted Series and Changes:Seasonally Adjusted Series:Changes in the Seasonally Adjusted Series:(' Lags from Concurrent Analyzed for ',a)(5x,5i5)Trend-Cycle Component and Changes:Trend-Cycle Component:Changes in the Trend Cycle Component:(' Forecast Lags Analyzed for Forecast Error History', ' Analysis:')(' Starting date for history analysis: ',a)(' Ending date for ',a,': ',a)history analysisseasonal adjustment history analysisregARIMA model history analysis(' Seasonal Adjustment Revisions Computed Using ',a, ' as Target.')ConcurrentFinal(' regARIMA coefficient estimates are ',a, ' during the history analysis.')fixedestimated(' Starting values are reset to the values estimated for ', 'the full span of data.')(' The following regressors are held fixed during the ', 'history analysis:')(5x,a:,' ',a:,' ',a:,' ',a:,' ',a)rgarma.f(/,' ERROR: Work array too small,',i4,'*',i4,'>',i6,'.')B(/,' ERROR: Number of observations after differencing ', 'and/or conditional AR', /,' estimation is',i4,', which is less than the ', 'minimum series length', /,' required for the model estimated,',i4,'.',/) Check automatic modeling options (reduce maxorder for automdl, or check models used with pickmdl) and try again.(/,' ERROR: Non linear work array too small',i6,'>',i6, '.')YK ARMAIGLSDY@Mb@@ǘ?Dioɴ?tF_PQrmatot.f(4x,a,t21,a,t36,a)kept none(a,a,a,a,a)deleted(auto)PLength-of-Leap YearPrmotrv.f(4x,a,t21,a,t36,a)deleted+ none(a,a,a,a,a)Prndsa.f(f21.0)000@@rngbuf.fSystem error: illegal buffer request,(a) ERROR: Input record longer than limit :roots.f(' WARNING: Not all zeros of the AR or MA polynomial were', 'found.')T2z!@??8Y@??$@???{Gzt?QPK T7 [](a,a,a,a,a)dateactionregressors--------------------(//,' Actions on regARIMA outlier regressors from full ', 'data span',//, 4x,'Ending Date',5x,'Action',9x,'Outliers',/, 4x,'-----------',5x,'------',9x,'--------')rvrghd.fTrading DayStock Trading DaySun(before(change for beforeSun I(starting(change for afterSun II1-Coefficient Trading Day1-Coefficient Stock Trading DaySat/SunSat/Sun ISat/Sun IIsavacf.f(a,i2)$diff=$sdiff=(a:,a,a,a,a:,a,a,a,a,a,a)LagSample_ACF2SE_of_ACF2Ljung-Box_Qdf_of_QP-valueSample_ACFSE_of_ACF--------------------------Sample_PACFS.E._of_PACFsavchi.f(a,a,': ',i4,2(1x,e22.15)).(a:,a,a,a,a,a,a)dateExt&Otl_LabelLS_Label------------------------------savd8b.f;(a,a,a,a,a,a,100(a,i2.2,a))overallnonlinearloglikelihoodarmareg(a:,100a)----------------(a,a,a,a,100(a,i2.2,a))savitr.fsavmdc.f(a,i3)ntcnum: (a,i3.3,': ',e22.15)tcnum.ntcden: tcden.8(a,e22.15)tcvar: nsnum: snum.nsden: sden.svar: nsanum: sanum.nsaden: saden.savar: ntrnum: trnum.ntrden: trden.trvar: irrvar: =(' regression{',/,' variables=(')[AOLSRpTCSOTLconstseasonalsincos[t/,td1coeftdtd1nolpyeartdnolpyearlomloqlpyeartdstock1coeftdstocklomstockeaster(' ',a)easterstocklaborthankaolstlrpsotc(before (change from before )///sceaster(starting )(' user=(')(' ',a)start=data=(('(t5,4e',i2.2,'.',i2.2,')')usertype=(6constanttdlomloqlpyeartdstocklomstockeasterlaborthanksaolsrpusereasterstocksceasterseasonaltcsoholidayholiday2holiday3holiday4holiday5transitory noapply=( td ao ls tc so holiday userseasonal userb=((' ',e24.10,a)feastermeans=noffffff?(a,f14.6) tcrate=(' }')(/,' arima{model=',/,' ',a)(' ',a,'=(')(' )')P\P\\x\\Ӳ\E\\)\(\\\@\\\7\\\@\\x\\Ӳ\E\\)\(\\C\R\\x\\Ӳ\E\\)\(\@\\\\\\@\\)\)\)\@\@\@\@\@\Y\savmdl.fsavmtx.f(1000a)Date----savotl.f(a:,a) Outliers identifed in this run: (5x,a,' (t=',f10.2,')')(a,i2)outlier.ao: outlier.ls: outlier.tc: outlier.so: outlier.rp: outlier.tls: outlier.user: outlier.total: autoout: No outliers identified(a,i6) Total number of outliers identified: none(a,a) Seasonal Spectral Peaks : TD Spectral Peaks : Seasonal Spectral Peaks (direct) : TD Spectral Peaks (direct) : Seasonal Spectral Peaks (indirect) : TD Spectral Peaks (indirect) : peaks.seas: peaks.td: peaks.seas.dir: peaks.seas.ind: peaks.td.dir: peaks.td.ind: savpk.fsavspp.f(a:,a,a,a,a)PosFrequency--------------------------savstp.f(a:,a,a,a,a)PosFrequency--------------------------.(a:,a,a)date-----------------------------savtbl.fsavtpk.f(a,a) For Peak Probability > 0.99 Seasonal Tukey Spectral Peaks : TD Tukey Spectral Peaks : 0.90 Peak Probability > Seasonal Tukey Spectral Peaks (direct) : TD Tukey Spectral Peaks (direct) : Seasonal Tukey Spectral Peaks (indirect) : TD Tukey Spectral Peaks (indirect) : peaks.tukey.seas: peaks.tukey.td: peaks.tukey.seas.ind: peaks.tukey.td.ind: peaks.tukey.p90.seas: peaks.tukey.p90.td: peaks.tukey.p90.seas.ind: peaks.tukey.p90.td.ind: x lagTC_WK_FilterSA_WK_FilterS_WK_FilterTR_WK_FilterIRR_WK_Filtersavwkf.f(1000a)--------------------------8??@/$?seatdg.f(a,': ',a)seatsadjyesnosfnocannotsignal extractiondoes notseasonal adjustment(' WARNING: Sliding spans analysis cannot be done when', ' SEATS ',a,' perform')(' a ',a,a) for a span of data..WARNING: History analysis for estimates derived from SEATS adjustments cannot be done when SEATS cannot perform a signal extraction.(2i5)(1x,e21.14)SA_Squ_Gain_SymetricqSA_Squ_Gain_ConcrTrn_Squ_Gain_SymetricsTrn_Squ_Gain_ConctSA_Time_Shift_ConcuTrn_Time_Shift_ConcvwSA_Filter_SymetricxSA_Filter_ConcyTrn_Filter_SymetriczTrn_Filter_Conc SEATS model (SEATS routines changed ARIMA model)seatsmdlNOTE: Model used for SEATS decomposition is different from the model estimated in the regARIMA modeling module of X-13A-S.cY(a,': ',i3)seats$nonseasonaldiffseats$seasonaldiffseats$nmodel(a,i2.2,3(a,e21.14)) Nonseasonal AR() - seats$AR$Nonseasonal$01$: Seasonal AR() - seats$AR$Seasonal$12$ Nonseasonal MA(seats$MA$Nonseasonal$01$ Seasonal MA(seats$MA$Seasonal$12$(a)8(a,':',f10.4,3x,a) Normality Test( Chi-Squared(2) )normalitytest(a,':',f10.4,3x,f10.4) SEATS KurtosisSEATSkurtosis SEATS SkewnessSEATSskewness(a,':',e20.10,3x,a) Residual SD Residual VariancevarsdvarresDurbin-WatsonSEATSdurbinwatsonNon-parametric Test for Residual Seasonality (Friedman)( Chi-Squared( )SEATSfriedman(/,' SEATS adjustment diagnostics cannot be saved when ', 'SEATS cannot perform', /,' a signal extraction.',/) Total Squared Error (trend)tsetrend Total Squared Error (seasonal)tseseasonal Total Squared Error (transistory)tsetransitory Total Squared Error (seas adj)tseseasadj(a,':',3(f10.4,1x),2x,a) Trend Variancevartrend Sadj Variancevarseasadj Irregular Variancevarirreg Seasonal Variancevarseasonal Concurrent estimation error (trend) Concurrent estimation error (S. A.)concesterr(a,i1,':',f10.4,3x,f10.4) Pct. Reduction Year pctreductionyr Ave. Value of Abs. Diff. in Annual Averagesavadaa(a,':',i4,3x,a) Significant Seasonal Periods in Historical Estimator Significant Seasonal Periods in Concurrent Estimator Significant Seasonal Periods in Forecast for Next Yearsigseashistsigseasconcsigseasfcstfinmodemultiplicativeadditive?8]W{/final trend component (SEATS)final trend cycle with constant value added (SEATS)final seasonal component (SEATS)final seasonal component (SEATS, saved as a percent if log transformation used)final irregular component (SEATS)final irregular component (SEATS, saved as a percent if log transformation used)final seasonally adjusted series (SEATS)final seasonally adjusted series with constant value added (SEATS)final transitory component (SEATS)final transitory component (SEATS, saved as a percent if log transformation used)final combined adjustment factors (SEATS)final combined adjustment factors (SEATS, saved as a percent if log transformation used)final trend component forecast decomposition (SEATS)final seasonal component forecast decomposition (SEATS)series forecast decomposition (SEATS)final seasonally adjusted series forecast decomposition (SEATS)final transitory component forecast decomposition (SEATS)final adjustment ratios (SEATS)total adjustment factors (SEATS)Wiener-Kolmogorov end filtercomponent modelspseudo innovations in trend-cyclepseudo innovations in seasonalpseudo innovations in transitory componentpseudo innovations in seasonally adjusted seriessquared gain of the symmetric seasonal adjustment filtersquared gain of the concurrent seasonal adjustment filtersquared gain of the symmetric trend filtersquared gain of the concurrent trend filtertime shift of the concurrent seasonal adjustment filtertime shift of the concurrent trend filtersymmetric seasonal adjustment filterconcurrent seasonal adjustment filtersymmetric trend filterconcurrent trend filterdifferenced original series after transformation, prior adjustment (SEATS)differenced final seasonally adjusted series (SEATS)differenced final trend (SEATS)sum of final seasonal component (SEATS)final cyclefinal long term trendstandard error of final seasonal component (SEATS)standard error of final seasonally adjusted series (SEATS)standard error of final trend component (SEATS)standard error of final transitory component (SEATS)final seasonally adjusted series adjusted for outliers (SEATS)final irregular component outlier adjusted (SEATS)Datab Z[~ ^_| XY}d \`abijlk+==2=+=serates.f(" N SDRev SDR1 SDRmq")(I3," ",G11.3," ",G11.3," ",G11.3)("SDRmqF=",G11.3)("SDRmqC=",G11.3)("SDRmqC2=",G11.3)("SDRmqPf=",G11.3)setamx.f(/,' ERROR: Unable to set up ARIMA model ',a,' for pickmdl', /,' automatic model selection procedure for the ', 'reason(s)',/,'given above.')ERROR: Default outlier critical value cannot be derived due to an internal error. Use the critical argument to set the outlier critical value. estimation error. Use the critical argumentto set the outlier?@^j?@ERROR: Default outlier critical value cannot be derived for an outlier span of one observation. Either use the critical argument to set the outlier critical value, or change thesetting of the defaultcritical argument.?@^j?@$setmdl.f(/,' ERROR: ',a,' polynomial with initial parameters', ' is noninvertible',/,' with root(s) inside the', ' unit circle. RESPECIFY model with',/, ' different initial parameters.',/)?(/,' ERROR: ',a,' polynomial with initial parameters', ' is noninvertible',/,' with root(s) on the ', 'unit circle. RESPECIFY model with',/, ' different initial parameters.',/)(' ',a,' Roots',/,' Root',t25,'Real',t31,'Imaginary', t44,'Modulus',t53,'Frequency',/,a)(' Root',i3,t18,4F11.4)(a)(/,' ERROR: ',a,' polynomial with initial parameters', ' is nonstationary',/,' with root(s) on or', ' inside the unit circle. RESPECIFY the',/, ' model with different initial parameters.', /)(/,' WARNING: ',a,' polynomial with initial parameters', ' is nonstationary', /,' with root(s) on or inside the unit ', 'circle. RESPECIFY the model', /,' with different initial parameters.',/)(\?Maximum number of DIFFARMA lags, , exceeded.ERROR: Maximum number of ARIMA coefficients, , exceeded. Reduce the model order.8setpt.f(' ',a,' parameter estimates:',t40,5f8.3)(t40,5f8.3)WARNING: No seasonal adjustment has been done because type=summary occurs in the x11 spec. Therefore no sliding spans analysis has been done. The unadjusted series from this spec file has been incorporated into the composite seasonal adjustment for each of the sliding spans.NOTE: Not enough data to produce sliding spans of length .NOTE: Not enough data to perform sliding spans analysis. Must be able to form at least two spans of length spans with at least 3 years of data. Must have at least 3 years of data in each span to perform sliding spans analysis for stable seasonal filters. Must be able to form at least two sliding spans.WARNING: Date of the first sliding spans comparison is set too early. This date will be reset so that it is one year after the starting date of the first span.J@sfmsr.f('1 Final Seasonal Filter Selection via GLOBAL MSR',/)(' *** Not enough data to continue, 3x5 seasonal filter ', 'selected ***')('autosf.msr',i2.2,': ',f6.2)(' Pass No. ',i2,': Global MSR = ',f6.2,', ',a3, ' seasonal filter selected.')(' Pass No. ',i2,': Global MSR = ',f6.2)('sfmsr: ',a3)@ @@SeasonalCombined Trigonometric Seasonal RegressorsUser-defined Seasonal Regressorssftest.f(' ',120(a))- ?@$@"@z|xYTD-STOCHASTICTD.StochTRANSITORYTRANSyOKXsigex.f(2X,'************************************',/, 2X,' PROBLEMS IN THE APPROX. ROUTINE ',/, 2X,' PLEASE E-MAIL THE INPUT FILE TO ',/, 2X,' x12a@census.gov ',/, 2X,'************************************') (2x,a)THE MODEL HAS NO ADMISSIBLE DECOMPOSITION( 2x,'MODEL CHANGED TO :',/,2x,'(',1x,i1,',',2x,i1,',',2x,i1,',' ,1x,')',4x,'(',1x,i1,',',2x,i1,',',2x,i1,1x,')')N ('()  !*+M&( //,4x,'MOVING AVERAGE REPRESENTATION OF ESTIMATORS', ' (NONSTATIONARY)')(//,4x,'The model for the components differs', ' from that of its theoretical MMSE estimator.',/,4x, 'The MA expressions of the estimators in terms of the ', 'observed series innovation',/,4x,'is given below.',/,4x, '(Negative lags represent future values;', ' positive lags represent past values.',/,4x, 'Lag 0 denotes the last observed period.')(//,4x,'The last column (the sum of the Psi-Weights)', ' should be zero',/,4x, 'for negative lags, 1 for lag=0, and equal to the', ' Box-Jenkins',/,4x,'Psi-Weights for positive lags.',/)(4x,'PSIEP(LAG), for example, represents the effect ', 'of the overall',/,4x, 'innovation at period (t-lag) on the estimator of the ', 'trend for period t.',/,4x, 'Similarly for the other components.',/)( //,3x,' LAG',6x,'PSIEP',7x,'PSIES',7x,'PSIEC',7x,'PSIEA',7x, 'PSIUE',13x,'PSIX',/)(3x,i4,5f12.4,5x,f12.4)L(//,2x,'DETERMINISTIC COMPONENT FROM regARIMA',/, 2x,'-------------------------------------')(14X,'NONE')(6X,a)LS (TREND-CYCLE)AO-TC (IRREGULAR)EASTER EFFECTTRADING DAY EFFECTREGRESSION VARIABLE SEPARATE REGRESSION EFFECT TREND-CYCLE REGRESSION EFFECT SEASONAL REGRESSION EFFECT IRREGULAR REGRESSION EFFECT OTHER REGRESSION EFFECT IN SA SERIES TRANSITORY REGRESSION EFFECTSOME OF THE FILTERS ARE NUMERICALLY UNSTABLE(6X,'DERIVATION OF THE FILTERS :',2X,A)(6x,'DERIVATION OF THE FILTERS :',/, 10x,'"',a,'"')Differenced Trend DPDifferenced SA SAirregular u /moments/acfes.m0(5(2x,g18.9))/moments/vares.m(A)(//,4x,'For all components it should happen that :', /,8x,'- Var(Component) > Var(Estimator)', /,8x,'- Var(Estimator) close to Var(Estimate)',/)(/,4x,'* If, for a component, Var(Estimator) >> ', 'Var(Estimate), there is UNDERESTIMATION', /,6x,'of the component.', //,4x,'* If Var(Estimator) << Var(Estimate), ', 'the component has been OVERESTIMATED.',/)/moments/ccfes.m(6(2x,g18.9))(//)(2x,'WEIGHTS FOR ',a,' ESTIMATOR FILTER (',a, ' realization)')ASYMMETRIC TREND CONCURRENTsemi-infinite(/,3(3X,'exp(B)',8x,'WEIGHTS',2X))(3(3X,I6,8X,F9.6))(//,' ',a,' OF ',a,' FILTER (',a,' realization)')TRANSFER FUNCTION AND PHASE DELAYASYMMETRIC TREND(/,14x,A5,3X,A13,3X,A13)WTransfp(w)phaseDELAYp(w)(13x,F6.3,3X,F13.8,3X,F13.8)ASYMMETRIC SA CONCURRENTASYMMETRIC SATransfsa(w)phaseDELAYsa(w)finiteSQUARED GAIN AND TIME SHIFT(/,18x,A,6X,A,5X,A)SqGainT(W)TimeShiftT(W)(/,' Warning: Time Shift may not be continuous since', ' Gain of partial filter is near zero for some w.')SqGainSA(W)TimeShiftSA(W)Trend P SA Series Irregular U 3451;?.;/089:()23*4(//,2x,'SERIES OF LEVELS (INCLUDING FORECASTS) HAVE',/,2x, 'BEEN CORRECTED FOR BIAS IN ',a,//)LEVELS FOR EVERY YEAR.(2x,'WARNING:',/,11x, 'IF ANNUAL BIASES ARE LARGE, THIS CORRECTION MAY AFFECT',/11x, 'THE STOCHASTIC PROPERTIES OF THE DECOMPOSITION.',/)OVERALL LEVEL.(//,3x,'ANNUAL AVERAGES',/, 3x,'---------------',/, 3x,'(including forecasting period)',/)(4x,'YEAR',11x,'SERIES',14x,'SA SERIES',12x, 'TREND-CYCLE',/)(4X,I4,9X,G12.4,9X,G12.4,10X,G12.4)(/,2x,'FULL PERIOD',4x,g12.4,9x,g12.4,10x,g12.4)(/,4x,'AVERAGE VALUE OF ABSOLUTE', /,4x,'DIFFERENCES IN ANNUAL AVERAGES :', /,4x,'(in % of average level)',/)(/,4X,a,2X,G12.3)ADJUSTED SERIES : TREND-CYCLE : (///,2x,'DIFFERENCES IN ANNUAL AVERAGES OF ', 'ORIGINAL SERIES,',/,2x,'SA SERIES AND TREND-CYCLE', ' ARE LARGE. TO AVOID DISTORSION OF',/,2x, 'THE STOCHASTIC PROPERTIES OF THE SERIES, IT SHOULD ', 'BE MODELLED',/,2x,'IN LEVELS.',//,2x,A, ' SHOULD BE RERUN WITH NO TRANSFORMATION.')X-13ARIMA-SEATS( ///' PART 4 : ESTIMATES OF THE COMPONENTS (LEVELS)',/, ' ---------------------------------------------',//)(/,4x,'THE SE ARE THOSE OF THE TOTAL ESTIMATION ERROR =', /,4x,'REVISION ERROR AND FINAL ESTIMATION ERROR.',/)(/,' PREADJUSTMENT COMPONENT', /,' Outliers and Other Deterministic Effects', //,' (from regARIMA)')( //,' ARIMA SERIES',/,' (Corrected by regARIMA)',/ ' "Original Series" FOR SEATS')(/,' SEASONAL COMPONENT ')(//,4x,'STOCHASTIC COMPONENT',/, 4x,'--------------------')(/,4x,'THE SE ARE THOSE OF THE TOTAL ESTIMATION ERROR =', /,4x,'REVISION ERROR AND FINAL ESTIMATION ERROR.')(/,' SEASONAL FACTORS (X 100)')(/,1X,'STANDARD ERROR OF ',a,/)SEASONAL FACTORS (X 100)SEASONAL(/,4x,'GIVEN THAT THE SEASONALITY IS NOT SIGNIFICANT, ', 'THE SEASONAL', /,4x,'COMPONENT ESTIMATE MAY WELL BE SPURIOUS')STOCHASTIC TD FACTOR (X 100)STANDARD ERROR OF STOCHASTIC TD COMP.TRANSITORY FACTORS (X 100)STANDARD ERROR OF TRANSITORY COMP.(/,A)(/,1X,A,/)STOCHASTIC TD COMPONENTTRANSITORY COMPONENT(/,' TREND-CYCLE')STANDARD ERROR OF TREND-CYCLE(//,' REAL-TIME ESTIMATORS OF ',a, ' (SEQUENCE OF CONCURRENT ESTIMATORS)')TREND-CYCLE(//,' REVISION FROM UPDATING REAL-TIME ',a, ' ESTIMATORS')(/,' SEASONALLY ADJUSTED SERIES')STANDARD ERROR OF SEASONALLY ADJUSTED SERIESSA SERIES(/,' IRREGULAR COMPONENT')(/,' IRREGULAR FACTORS (X 100)')!  (//,2X,'FINAL SA SERIES WITH REVISED YEARLY',/)"?vIh%<=KH9|=`P:<6S:??Y@@a@:0yE>wJ?<nc (/,12x,'CROSSCORRELATION BETWEEN STATIONARY', ' TRANSFORMATION OF ESTIMATORS',/)(35X,'ESTIMATOR',12X,'ESTIMATE',8x,A4,/)SE Var.TREND-CYCLE/SEASONAL SEASONAL/IRREGULAR TREND-CYCLE/IRREGULAR (A,a,'/',A)irregular(/,4x,'(**) : unreliable SE estimate.')(//,10x,'For all pairs of components, the ', 'crosscorrelation between', /,10x,'the estimators and that between the estimates ', 'should be', /,10x,'broadly in agreement.')(/,4x,'COMPARISON BETWEEN THEORETICAL AND EMPIRICAL ', 'CROSSCORRELATION',/)TREND-CYCLE/SEASONAL SEASONAL/IRREGULAR TREND-CYCLE/IRREGULARIRREGULAR(/)|=?@(//,12x,'Crosscovariance Between Stationary', ' Transformation Of Estimators In Units Of Var(A)',/)(35X,'Estimator',12X,'Estimate',8x,A4,/)Trend-Cycle/Seasonal Seasonal/Irregular Trend-Cycle/Irregular(4X,A26,7X,F10.3,10X,F10.3,8x,a) (**) (4X,A26,7X,F10.3,10X,F10.3,4x,F10.3)E?(4X,A26,' : OK')(4x,a,' : NOT IN AGREEMENT',/,27x, '(Indicates model misspecification)')(4x,A,' and ',A,' component estimators', ' can be seen as approximately uncorrelated.')(4x,A,' and ',A,' component estimators', ' are mildly correlated.')(4x,'MMSE estimation induces substantial ', 'correlation between the estimators',/,4x, 'of the ',A,' and ',A,' components.')?('"',A,'"')(' LAG',12X,'P',14X,'N',14X,'S',14X,'U',14X,'C')(I4,5X,5(F14.11,X))vIh%v@@^@?Q?f@Qx`@XO^@N OPQRSsigsub.f( ///,' PART 3 : ERROR ANALYSIS',/,' -----------------------',//)( //,30x,'ESTIMATION ERROR VARIANCE'/,30x,' (In units of Var(a))' ,//34x,'TREND-CYCLE',2x,'SA SERIES',//2x,'FINAL ESTIMATION' ,15x,f6.3,10x,f6.3,/,2x,'ERROR',a,//2x,'REVISION IN CON-' ,15x,f6.3,10x,f6.3,/,2x,'CURRENT ERROR',//2x,'TOTAL ESTIMATION' ,15x,f6.3,10x,f6.3,/,2x,'ERROR (CONCURRENT',/,2x,'ESTIMATOR)') (SEMI-INFINITE)( //,' ',25x,'FINAL ESTIMATION ERROR',21x,'REVISION IN', ' CONCURRENT ESTIMATOR'//' ACF (LAG)',12x,' TREND-CYCLE ',5x, 'SA SERIES',14x,' TREND-CYCLE ',4x,'SA SERIES'/)(1x,i7,2x,12x,f8.3,10x,f8.3,17x,f8.3,8x,f8.3)(/,' ','VAR.(*)',2x,12x,f8.3,10x,f8.3,17x,f8.3,8x,f8.3)( ////6x,'TOTAL ESTIMATION ERROR (CONCURRENT ESTIMATOR)',/6x, '---------------------------------------------',//8x,'ACF (LAG)' ,5x,' TREND-CYCLE ',4x,'SA SERIES'/)(2x,i10,11x,f8.3,8x,f8.3)(/,' ',6x,'VAR.(*)',9x,f8.3,8x,f8.3)(//,' ',' (*) IN UNITS OF VAR(A)')( ///,' ','VARIANCE OF THE REVISION ERROR (*)',/,' ', '------------------------------',//' ADDITIONAL',12x, ' TREND-CYCLE ',4x,' SA SERIES'/' PERIODS'//)(2x,i5,10x,2(7x,g11.4))( ///,' ',' PERCENTAGE REDUCTION IN THE STANDARD ERROR', ' OF THE REVISION AFTER ADDITIONAL YEARS'/ ' (COMPARISON WITH CONCURRENT ESTIMATORS)'///)(3x,'AFTER',i2,' YEAR',7x,g11.4,7x,g11.4)x( ///,' ','VARIANCE OF THE REVISION ERROR FOR THE ', 'SEASONAL COMPONENT (ONE YEAR AHEAD ADJUSTMENT)',/,' ', '---------------------------------------', '----------------------------------------------',// ' PERIODS AHEAD',10x,'VARIANCE (*)'/)(2x,i8,15x,g11.4)( ///,' ','AVERAGE PERCENTAGE REDUCTION IN RMSE FROM', ' CONCURRENT ADJUSTMENT',g11.4)abcdefghixyzjkl{( //,' ',12x,'LOGS DECOMPOSITION OF THE SERIES: RECENT', ' ESTIMATES'/' ',12x,'---------------------------------------', '-----------'//1x,'PERIOD',5x,'SERIES ',22x,' TREND-CYCLE',37x, 'SA SERIES',//30x,'ESTIMATE',10x,'STANDARD ERROR',20x,'ESTIMATE' ,10x,'STANDARD ERROR'/46x,'TOTAL',6x,' OF REVISION',27x, 'TOTAL',6x,' OF REVISION'/)( //,' ',12x,'ADDITIVE DECOMPOSITION OF THE SERIES:', ' RECENT ESTIMATES'/' ',12x, '---------------------------------------','---------------'//1x, 'PERIOD',5x,'SERIES ',22x,' TREND-CYCLE',37x,'SA SERIES',//30x, 'ESTIMATE',10x,'STANDARD ERROR',20x,'ESTIMATE',10x, 'STANDARD ERROR'/46x,'TOTAL',6x,' OF REVISION',27x,'TOTAL' ,6x,' OF REVISION'/)( 2x,i4,2x,g11.4,7x,g11.4,4x,g11.4,4x,g11.4,12x,g11.4, 4x,g11.4,4x,g11.4)( //,' STANDARD ERROR OF',23x,g11.4,42x,g11.4,/' FINAL ESTIMATOR')( /,/1x,'PERIOD',20x,'SEASONAL',//18x,'ESTIMATE',10x, 'STANDARD ERROR'/33x,'TOTAL',6x,' OF REVISION'/)( 2x,i4,7x,g11.4,4x,g11.4,4x,g11.4,12x,g11.4,4x,g11.4,4x,g11.4)(//,' STANDARD ERROR OF',15x,g11.4,/,' FINAL ESTIMATOR')( /,/1x,'PERIOD',20x,'SEASONAL',45x,' TRANS. ',//18x,'ESTIMATE' ,10x,'STANDARD ERROR',20x,'ESTIMATE',10x,'STANDARD ERROR'/33x, 'TOTAL',6x,' OF REVISION',27x,'TOTAL',6x,' OF REVISION'/)( //,' STANDARD ERROR OF',10x,g11.4,42x,g11.4,/, ' FINAL ESTIMATOR')( //,' ',12x,'FORECAST OF THE STOCHASTIC SERIES ', 'AND COMPONENTS (LOGS)'/,' ',12x, '----------------------------------','---------------------'/ /1x,'PERIOD',5x,'SERIES ',32x,' TREND-CYCLE',37x,'SA SERIES',// 10x,'FORECAST',8x,'S.E.',10x,'FORECAST',10x,'STANDARD ERROR' ,20x,'FORECAST',10x,'STANDARD ERROR'/56x,'TOTAL',6x, ' OF REVISION',27x,'TOTAL',6x,' OF REVISION'/)( //,' ',12x,'FORECAST OF THE STOCHASTIC SERIES ','AND COMPONENTS' /,' ',12x,'----------------------------------','--------------'/ /1x,'PERIOD',5x,'SERIES ',32x,' TREND-CYCLE',37x,'SA SERIES',// 10x,'FORECAST',8x,'S.E.',10x,'FORECAST',10x,'STANDARD ERROR' ,20x,'FORECAST',10x,'STANDARD ERROR'/56x,'TOTAL',6x, ' OF REVISION',27x,'TOTAL',6x,' OF REVISION'/)mnrstuvwopq( 2x,i4,2x,g11.4,2x,g11.4,4x,g11.4,4x,g11.4,4x,g11.4, 12x,g11.4,4x,g11.4,4x,g11.4)( //,' ',/1x,'PERIOD',20x,' SEASONAL',//18x,'FORECAST',10x, 'STANDARD ERROR',/33x,'TOTAL',6x,' OF REVISION'/)(2x,i4,7x,g11.4,4x,g11.4,4x,g11.4)(/,30x,'DUE TO THE APPROXIMATION, THE S.E.',/, 30x,'OF THE COMPONENT MAY BE UNRELIABLE',/)( //,' ',/1x,'PERIOD',20x,' SEASONAL',45x,'TRANS.',//18x, 'FORECAST',10x,'STANDARD ERROR',20x,'FORECAST',10x, 'STANDARD ERROR'/33x,'TOTAL',6x,' OF REVISION',27x,'TOTAL' ,6x,' OF REVISION'/)( 2x,i4,7x,g11.4,4x,g11.4,4x,g11.4,12x,g11.4,4x,g11.4,4x,g11.4)(/,30x,'DUE TO THE APPROXIMATION, THE S.E.',/, 30x,'OF THE COMPONENT MAY BE UNRELIABLE',/)(//,' ','SAMPLE MEANS',/,' ','------------'/)( 15x,'COMPLETE PERIOD',4x,'LAST 12 OBSERVATIONS'/' SERIES ' ,6x,g11.4,6x,g11.4/' TREND-CYCLE',3x,g11.4,6x,g11.4/' SA SERIES' ,5x,g11.4,6x,g11.4/' SEASONAL',6x,g11.4,6x,g11.4)( 15x,'COMPLETE PERIOD',4x,'LAST THREE YEARS'/' SERIES ' ,6x,g11.4,6x,g11.4/' TREND-CYCLE',3x,g11.4,6x,g11.4/' SA SERIES' ,5x,g11.4,6x,g11.4/' SEASONAL',6x,g11.4,6x,g11.4)(6X,'BIAS PARAMETER =',I2)vIh%<=ؗҜ<?Y@|=(@& .>??@(//,2x,'SIGNIFICANCE OF SEASONALITY',/,2x, '---------------------------',/)(//,4x,'FINAL ESTIMATION ERROR VARIANCE ', 'OF SA IS ZERO' ,/,4x,'SEASONAL SIGNIFICANCE TEST SKIPPED')(4x,'Significance of seasonality is ', 'assessed using the variances of the',/,4x, 'total estimation error, which includes the ', 'error in the preliminary estimator',/,4x, '(the revision error) and the error in the final estimator.')(4x,'Because the S.E. of the seasonal ', 'component estimator varies (it reaches a minimum',/,4x, 'for historical estimation and a maximum for the most ', 'distant forecast), the significance of seasonality',/,4x, 'will be different for different periods.',/,4x, 'An extreme example would be a series showing ', 'significant seasonality for historical estimates,',/,4x, 'that is poorly captured concurrently, and useless for ', 'forecasting.')(//,8x,'SEASONAL',22x,'NUMBER OF PERIODS IN A YEAR THAT' ,/,8x,'COMPONENT',21x,'HAVE SIGNIFICANT SEASONALITY',/,44x, '90%',10x,'95%')(/,4X,'HISTORICAL ESTIMATOR',19X,I3,10X,I3)(/,4X,'PRELIMINARY ESTIMATOR',18X,I3,10X,I3)(4X,'FOR LAST YEAR')(/,4X,'FORECAST FOR NEXT YEAR',17X,I3,10X,I3)(//,4x,'For the present series :',/,4x, '------------------------',/)(6x,'FINAL OR HISTORICAL ESTIMATION SHOWS ', 'CLEARLY SIGNIFICANT SEASONALITY IN THE SERIES.',/)(6x,'FINAL OR HISTORICAL ESTIMATION SHOWS ', 'BORDERLINE SIGNIFICANT SEASONALITY IN THE SERIES.',/)(6x,'FINAL OR HISTORICAL ESTIMATION SHOWS ', 'NOT SIGNIFICANT SEASONALITY IN THE SERIES.',/)(6x,'CONCURRENT AND PRELIMINARY ', 'ESTIMATION SHOW CLEARLY SIGNIFICANT SEASONALITY ', 'FOR RECENT PERIODS (LAST YEAR).',/)(6x,'CONCURRENT AND PRELIMINARY ', 'ESTIMATION SHOW BORDERLINE SIGNIFICANT SEASONALITY ', 'FOR RECENT PERIODS (LAST YEAR).',/)(6x,'CONCURRENT AND PRELIMINARY ', 'ESTIMATION SHOW NOT SIGNIFICANT SEASONALITY ', 'FOR RECENT PERIODS (LAST YEAR).',/)(6x,'ONE-YEAR AHEAD FORECAST FUNCTION ', 'CONTAINS CLEARLY SIGNIFICANT SEASONALITY.',/)(6x,'ONE-YEAR AHEAD FORECAST FUNCTION ', 'CONTAINS BORDERLINE SIGNIFICANT SEASONALITY.',/)(6x,'ONE-YEAR AHEAD FORECAST FUNCTION ', 'CONTAINS NOT SIGNIFICANT SEASONALITY.',/)(/,20x,'"SEASONALITY IS NOT PRESENT OR IS ', 'TOO WEAK TO BE ACCURATELY CAPTURED.',/,20x, 'THE SERIES, POSSIBLY, SHOULD NOT BE SEASONALLY ADJUSTED.', /,20x,'TO OBTAIN THE TREND-CYCLE, ', 'SIMPLY LET THE SEASONAL COMPONENT BE ADDED TO',/,20x, 'THE IRREGULAR IN THE PRESENT RUN, OR TRY A ', 'NON-SEASONAL MODEL."',/)( ///' CONFIDENCE INTERVAL AROUND A SEASONAL FACTOR OF 100',/ ' ---------------------------------------------------',//28x, 'FINAL ESTIMATOR',24x,'CONCURRENT ESTIMATOR'/' 95%'/ ' CONFIDENCE',12x,2g11.4,20x,2g11.4,/' INTERVAL'//' 70%'/ ' CONFIDENCE',12x,2g11.4,20x,2g11.4,/' INTERVAL'/)( ///' CONFIDENCE INTERVAL AROUND A SEASONAL COMPONENT OF 0',/ ' ----------------------------------------------------',//20x, 'FINAL ESTIMATOR',20x,'CONCURRENT ESTIMATOR'/' 90%'/ ' CONFIDENCE',12x,2g11.4,20x,2g11.4,/' INTERVAL'//' 70%'/ ' CONFIDENCE',12x,2g11.4,20x,2g11.4,/' INTERVAL'/)Y@d;O?:0yE>@ffffff?@?@?@@@?simul.f('ON TOO BIG')?Expected NAME=VALUE or NAME=(LIST) not ""No closing brace "}" on specification, ""nosmpeak.f(a,'.',a,': ',a)nopeak(a,'.',a,': ',f6.1,' ',a)+ .domspcdrv.f(a,a)diffspec: yes(a,i4)diffspecorder: diffspecstart: no=(a,'.tukey.m: ',i5)ERROR: Spectral plot for the logged original series cannot be done for a series with values less than or equal to zero.ERROR: Spectral plot for the logged seasonally adjusted series cannot be done for a seasonal adjustment with values less than or equal to zero.NOTE: Spectral plot for the seasonally adjusted series cannot be done when SEATS cannot perform a signal extraction.differencedundifferenceddifferenced, transformedundifferenced, transformedWARNING: Visually significant seasonal and trading day peaks have been found in one or more of the estimated spectra.trading day and seasonalseasonaltrading dayWARNING: At least one visually significant peak has been found in one or more of the estimated spectra.(/,' Rerun the input file without the output ', 'suppression option',/, ' (-n flag) for more details.')(//,' Visually significant residual ',a,' peaks have been', /,' found in the spectral ',a,' of the following series', ' starting in ',a,':',/)plotplots(10x,a,' (',i1,' Seasonal and ',i1,' Trading Day peaks)',/)(10x,a,' (',i1,' Trading Day peak(s))',/)(10x,a,' (',i1,' Seasonal peak(s))',/)(SEATS)(Table E2)(Table D11) seasonally adjusted series Modified irregular component (Table E3)Stochastic irregular component (SEATS)(//,' WARNING: Series should not be a candidate for ', 'seasonal adjustment',/, ' because the spectrum of the',a,/ ' has no visually significant seasonal peaks.')(/,' If this is a component series of an ', 'indirectly adjusted',/, ' composite series, consider using type = ', 'trend or type = summary',/, ' in the x11 spec.')orisaindsairrindirr10*LOG(SPECTRUM)10*LOG(PERIODOGRAM)SPECTRUMPERIODOGRAMG 0 of the Spectrum estimated from to . . Spectrum estimated from G 1 Seasonally Adjusted Data (SEATS). Seasonally Adjusted Data (Table E2). Indirect Seasonally Adjusted Data (Table E2). indirect seasonally adjusted data (Table D11). seasonally adjustedG.1 indirect seasonally adjusted data (SEATS). Spectrum estimated from data (Table E2). Spectrum estimated from G 2 of the Stochastic Irregular (SEATS). of the Modified Irregular (Table E3). of the Indirect Modified Irregular (Table E3).ERROR: Spectral plots currently can only be generated for monthly or quarterly time series.=g(a,'.tukey.m: ',i5)WARNING: Visually significant seasonal and trading day peaks have been found in the estimated spectrum of the SEATS extended residuals. been found in the estimated spectrum of the regARIMA residuals.trading day and seasonalWARNING: At least one visually significant trading day peak has been found in the estimated spectrum of the SEATS extended residuals. found in the estimated spectrum of the regARIMA residuals.trading dayWARNING: At least one visually significant seasonal peak has been found in the estimated spectrum of the SEATS extended residuals. in the estimated spectrum of the regARIMA residuals.seasonalSEATS extended residualsregARIMA model residuals(//,2x,a,'isually significant residual ',a,' peaks ',a, ' been', /,' found in the spectral plot of the following series', ' starting in ',a,':',/)Vhave(10x,a,' (',i1,' Seasonal and ',i1,' Trading Day peak(s))', /)At least one vhas(10x,a,' (',i1,' Trading Day peak(s))',/)(10x,a,' (',i1,' Seasonal peak(s))',/)extrsdrsd10*LOG(SPECTRUM)10*LOG(PERIODOGRAM)(//) of the SEATS extended residuals. of the regARIMA model residuals. Spectrum estimated from to . spcrsd.f@??' @?@@special.fError MaxItera too small in BetaCfra?h䌤/Hz>@??@??@(//,6x,A,/)(/,10x,'MODE = ',F12.2, ' years cycle')(/,10x,'MODE = INF years cycle')(/,10x,'MEAN = ',F12.2, ' years cycle')(/,10x,'MEAN = INF years cycle')(/,10x,'MEDIAN = ',F12.2, ' years cycle',//)(/,10x,'MEDIAN = INF years cycle',//):0yE>?Uk@$@=^@H?`??`?AT--ncY@Xdo;L??Gz????YESNO ("Overall test for residual seasonality ")(' Autocorrelation function evidence : ',A3)(' Non-parametric evidence',11x,': ',A3)(' Spectral evidence',17x,': ',A3)(' Residual seasonality detected in ', 'seasonally adjusted series')(" Mild evidence of residual seasonality ", "detected in seasonally adjusted series")(' No residual seasonality detected in ', 'seasonally adjusted series')DAT (///,'FACTORIZATION OF THE MA POLYN FOR THE COMPONENTS',/, '-------------------------------------------------')MA ROOTS OF TREND-CYCLElETHE SPECIFICATION OF SOME OF THE MODELS MAY BE UNRELIABLEMA ROOTS OF SEASONALmMA ROOTS OF TD-STOCHASTIC MA ROOTS OF TRANSITORY nMA ROOTS OF SEASONALLY ADJUSTED SERIES&o(/6x,'DERIVATION OF THE COMPONENT MODELS :', 2x,a)(/6x,'DERIVATION OF THE COMPONENT MODELS :',/,10x,'"',a, '"')( ///,/,' ',20x,'MODELS FOR THE COMPONENTS',/,21x,25('-'),///)(///,' TREND-CYCLE NUMERATOR (MOVING AVERAGE POL.)')(12f11.5)(' TREND-CYCLE DENOMINATOR (AUTOREGRESSIVE POL.)')(' INNOV. VAR. (*)',f12.6)(/,2X,'(*) IN UNITS OF VAR(A)')(/,a,'The innovation variance of the ',a,' is ',a,',',/, ' an indication that the model is not suitable for ', 'signal extraction',a,/, a,'Examine the arima model used for this ', 'decomposition for possible unit roots,',/, ' and try another model',a) trendgreater than one.less than zero(///,' SEAS. NUMERATOR (MOVING AVERAGE POL.)')(' SEAS. DENOMINATOR (AUTOREGRESSIVE POL.)')seasonal(///,A,' NUMERATOR (MOVING AVERAGE POL.)')(' ',A,' DENOMINATOR (AUTOREGRESSIVE POL.)') transitory(///,' IRREGULAR')(' VAR. (*) ',f12.5)( ///,' SEASONALLY ADJUSTED NUMERATOR ','(MOVING AVERAGE POL.)')( /,' SEASONALLY ADJUSTED DENOMINATOR (AUTOREGRESSIVE POL.)')seasonal adjustmentNO ADMISSIBLE?( ////,4x,' DECOMPOSITION INVALID'//,10x, '*****************************',/,12x, 'THE MODEL IS APPROXIMATED',/,10x, '*****************************',/)( ////,' DECOMPOSITION INVALID,IRREGULAR SPECTRUM NEGATIVE'/, ' TRY ANOTHER MODEL OR, FOR AN APPROXIMATION,', ' SET NOADMISS=1.' )( //,4x,' MA ROOTS OF TREND ADJUSTED SERIES'/,4x, ' --------------------------------------')( /,' ','THE LENGTH OF THE MA DOESN''T MATCH WITH THE ACF')(/,5x,'TOTAL SQUARED ERROR=',d15.7)( //,4x,' MA ROOTS OF CYCLE ADJUSTED SERIES'/,4x, ' --------------------------------------').sum('(1 +',f5.2,'B')('(1 -',f5.2,'B')(A,' +',f5.2,'B^',i1)(A,' -',f5.2,'B^',i1)) (1-B)(A,'(1-B)^',i1) p(t) = (A,' (1 +',f5.2,'B')(A,' (1 -',f5.2,'B')) ap(t), ap(t)~N(0,(A,G12.4)) niid (A,' +',f5.2,'B^',i2)(A,' -',f5.2,'B^',i2) S s(t) = s(t) = (A," -"f5.2,"B^",i1)(A,' -'f5.2,'B^',i2) as(t),(A,' as(t)~N(0,',G13.6)('(1') (1-B)^(A ,i1) n(t) = (A,' (1') an(t)(A,', an(t)~N(0,',G13.6)('(1 ') c(t) = ac(t),(A,' ac(t)~N(0,',G13.6)("u(t) = N(0,",G13.6)(i2)(A,4x,f5.2)(A,4x,i5)(A,3x,i5)(A,x,A,5x,G13.6)(A,3x,f5.2)(A,x,A,3x,G13.6)(A)(A,A,3x,G13.6,6x,f12.6)(/,' HARMONIC FUNCTIONS')( //' F(X) F(X)'/' ____ = ________________'/ ' H(X) T(X) C(X) S(X) '//)(/,' F(X)'/)(12f11.4)(/,' T(X)'/)(/,' C(X)'/)(/,' S(X)'/)(/,' N(X), FORMED FROM THE PRODUCT T(S)C(X)'/)( /,' H(X), FORMED FROM THE PRODUCT',' T(X)C(X)S(X) = N(X)S(X)' /)( //' F(X) = QT(X) + RT(X)'/' ____ _____'/ ' H(X) H(X) '//' QT(X) QUOTIENT ')(' ',8(f11.4,2x))(/,' RT(X) REMAINDER ')( ///,' RT(X) = U(X) + V(X)'/' +________ ____ ____'/ ' N(X)S(X) N(X) S(X)'//' U(X)')(/,' V(X)')( ///,' DUM(X) = RT(X) - U(X)S(X) - V(X)N(X).', ' THIS SHOULD BE ZERO'//7(2x,f11.4))( ///,' U(X) = UT(X) + UC(X)'/' +________ _____ _____'/ ' T(X)C(X) T(X) C(X)'//' UT(X)')(/,' UC(X)')( ///,' DUM(X) = U(X) - UT(X)C(X) - UC(X)T(X).', ' THIS SHOULD BE ZERO'//7(2x,f11.4))( ///,' RT(X) = UT(X) + UC(X)'/'+________ _____ _____'/ ' T(X)C(X) T(X) C(X)'//' UT(X)')( ///,' DUM(X) = RT(X) - UT(X)C(X) - UC(X)T(X).', ' THIS SHOULD BE ZERO'//7(f11.4))( ///,' RT(X) = V(X) + UC(X)'/'+________ ______ ______'/ ' S(X)C(X) S(X) C(X)'//' V(X)')( ///,' DUM(X) = RT(X) - V(X)C(X) - UC(X)S(X).', ' THIS SHOULD BE ZERO',//,7(2x,f11.4))( ///,' RT(X) = UT(X) + V(X)'/'+________ _____ _____'/ ' T(X)S(X) T(X) S(X)'//' UT(X)')(/,' V(X)')( ///,' DUM(X) = RT(X) - UT(X)S(X) - V(X)T(X).', ' THIS SHOULD BE ZERO'//7(f11.4))( //, 1x, a, //, 10(8(f11.4,1x),/) )UT(X)V(X)UC(X)( ///, ' DUM(X) = F(X)-V(X)T(X)C(X)-UT(X)S(X)C(X)-UC(X)S(X)T(X).', ' THIS SHOULD BE ZERO', //, 10(8(g12.5,1x),/) )( /,' LOCAL ',6x,'FREQUENCY',6x,'CONVERGENCE'/' MINIMA',6x, '(RADIANS)',6x,' TEST'//)(' SEASONAL SPECTRUM.LOCAL MINIMA'/)(' ',f9.6,4x,f7.4,11x,i2)(/,' MINIMUM MINIMORUM'//f11.6)(//,' ',A,' SPECTRUM. SIMPLE MINIMUM'/)(//' TREND-CYCLE SPECTRUM. SIMPLE MINIMUM'/)(////, ' DECOMPOSITION INVALID,SOME SPECTRUM NEGATIVE'//, 10x,'*****************************',/,12x, 'THE MODEL IS APPROXIMATED',/,10x, '*****************************',/)(/,1x, '***********************************************', '*********************',/,1x, 'NUMERATOR OF THE MODEL IS NEW-APPROXIMATED AND THE ', 'RESIDUALS RE-COMPUTED',/,1x, '***********************************************', '*********************')APPROXIMATED MODEL MA (///,"MA APPROXIMATE MODEL")ư>B (A,///)=Y(////, ' DECOMPOSITION INVALID,SOME SPECTRUM NEGATIVE'//, 10x,'*****************************',/,12x, 'THE MODEL IS APPROXIMATED',/,10x, '*****************************',/)J( ////,' DECOMPOSITION INVALID,IRREGULAR SPECTRUM NEGATIVE'/, ' TRY ANOTHER MODEL OR, FOR AN APPROXIMATION, SET NOADMISS=1.' )spectrum.fQk"@{G8@33333&@[{Κ?& .>@PERT! @PERT!@$@ QPK T7.: Indirect seasonal adjustment.NOTE: Sliding spans percentages cannot be stored in a separate diagonstics file when absolute differences of additive adjustments are analyzed.NOTE: Sliding spans percentages cannot be saved to a log file when absolute differences of additive adjustments are analyzed. Seasonal FactorsTrading Day FactorsFinal Seasonally Adjusted SeriesMonth-to-Month Changes in SA SeriesYear-to-Year Changes in SA SeriesQuarter-to-Quarter Changes in SA Series8(//,' S 1. ',a,a,' means of Seasonal Factors for ',a,a,/, 8x,'(movements within a ',a,' should be small)')(//,' S 1. ',a,a,' means of Implied Adjustment Factors ', 'for ',a,a,/,8x,'(movements within a ',a,' should be ', 'small)')(//,' S 2. Percentage of ',a,'s flagged as unstable',a,/)('s2.pct: ',a)yes(/,5X,'Range of seasonal factors is too low for ', 'summary sliding spans measures to be reliable.', /,5x,'Summary sliding spans statistics not computed.')no234ssap.f NT ssfnot.f(a,', TP, ',i1,a1)SCIE(' ',a2,', ',i1,a1,' ')(' TP, ',i1,a1,' ')(' ',i1,a1,' ') SC, TP IE, TP TP SC IE yes??? nossftst.f(//,5x,'Summary of tests for stable and moving ', 'seasonality from table D8 for each span',/) ('(28x,',i1,'(7x,a6))')('(5x,a20,6x,',i1,'(2x,f8.2,3x))')(' ')('(5x,a,24x,',i1,'(2x,f8.2,3x))')m7('(5x,a,',i1,'(8x,a3,2x))')Identifiable seasonality?(/,10x,'yes = Identifiable seasonality probably present',/, 10x,'??? = Identifiable seasonality probably not present', /,10x,' no = Identifiable seasonality not present',//)('(a,',i1,'(3x,f8.2))')ssfstab:ssfmov:ssm7:('(a,',i1,'(8x,a3))')ssident:@@@"@8Maximum Absolute Differences across spansMaximum Percent Differences across spanssshist.f(/,' Breakdown of the maximum percentage differences ', 'of the ',a,/,' for flagged ',a,'s.',/)(/,' Breakdown of the maximum percentage differences ', 'of the',/,2x,a,' for flagged ',a,'s.',/) :(i1)(' ',a,' Greater than or equal to ',f4.1,'% but less ', 'than ',f4.1,'% :',1x,i3)(' ',a,' Greater than or equal to ',f4.1,'%',t62,':',1x, i3,/)('s3.',a,'.thist',i1,':',2x,f4.1,2x,f4.1,2x,i3)('s3.',a,'.thist4:',2x,f4.1,8x,i3)P(before (change from before (starting NOTE: The following change of regime regression variables are not defined for at least one year of one of the spans of the sliding spans analysis: Change of regime regressor will be fixed.NOTE: The following change of regime regression variables could cause singularity problems in the regression matrix for at least one of the spans of the sliding spans analysis:NOTE: Since a model span is used, model parameters will be held fixed.Qe (???4NOTE: Seasonally adjusted values for at least one ofthe spans was less than or equal to zero. The sliding spans analysis will be calculated from the maximum differences of the seasonally adjusted series rather than the implied adjustment factors.NOTE: The user defined regressors listed below were held fixed for at least one span during the sliding spans analysis: (a,e15.8)bssap:essap:(//,' Sliding spans analysis: Indirect seasonal ', 'adjustment',/)('indsspans: ',a)yesNOTE: The indirect seasonal adjustment for at least one of the spans was less than or equal to zero. The sliding spans analysis will be calculated from the maximum differences of the indirect seasonally adjusted series rather than the implied adjustment factors.no(/,' NOTE: Different span lengths were used for the ', 'sliding spans analysis ', /,' of the component seasonal adjustments.',/, /,' Sliding spans analysis of the indirect ', 'seasonal adjustments will not', /,' be produced. Use the length argument of the ', 'slidingspans spec ', /,' to ensure an appropriate span length is ', 'specified for each ', /,' of the component spec files.')(/,' NOTE: The number of sliding spans used for the ', 'sliding spans analysis ', /,' has changed for one of the components in the ', 'composite seasonal adjustment.',/, /,' Sliding spans analysis of the indirect ', 'seasonal adjustments will not', /,' be produced. Check the numspan argument', ' of the slidingspans spec ', /,' to ensure the same number of sliding spans is ', 'specified for each ', /,' of the component spec files.')(/,' NOTE: Composite seasonal adjustment performed with ', i3,' components, ', /,' but the indirect seasonal adjustment for the', ' sliding spans', /,' was updated for none of the components.',/, /,' Sliding spans analysis of the indirect ', 'seasonal adjustments will not', /,' be produced. Ensure that a slidingspans spec', ' is present in the', /,' spec files of all the components.')(/,' NOTE: Composite seasonal adjustment performed with ', i3,' components, ', /,' but the indirect seasonal adjustment for the', ' sliding spans', /,' was updated for only ',i3,' components.',/, /,' Sliding spans analysis of the indirect ', 'seasonal adjustments will not', /,' be produced. Check for errors in the ', 'sliding spans analysis of the', /,' components, and ensure that a slidingspans spec', ' is present in the', /,' spec files of all the components.')(/,' NOTE: A different span length was specified for ', 'the sliding spans analysis', /,' of the direct seasonal adjustment of the ', 'composite than was used for', /,' the component seasonal adjustments.',/, /,' Sliding spans analysis of the indirect ', 'seasonal adjustments will not', /,' be produced. Use the length argument of the ', 'slidingspans spec ', /,' to ensure the same span length is used for', ' sliding spans analysis ', /,' of the direct seasonal adjustment and the ', 'component adjustments.')(/,' NOTE: A different number of sliding spans was ', 'specified for the', /,' sliding spans analysis of the direct seasonal ', 'adjustment of the', /,' composite than was used for the component', ' seasonal adjustments.',/, /,' Sliding spans analysis of the indirect ', 'seasonal adjustments will not', /,' be produced. Use the length argument of the ', 'slidingspans spec ', /,' to ensure the same span length is used for', ' sliding spans analysis ', /,' of the direct seasonal adjustment and the ', 'component adjustments.')sspdrv.fssphdr.f(a,': ',a)sspansyes('ssa: ',4I5)('sscut: ',5F7.2)sstdnossdiff(//,' Sliding spans analysis',//, ' S 0. Summary of options selected for this run',//)(//,' Sliding spans analysis:Direct seasonal adjustment', //,' S 0. Summary of options selected for this run',//)(set by user) (' ',a,' of spans : ',i5,3x,a)NumberLength(' Month of first observation in first span : ',i5,/, ' Year of first observation in first span : ',i5)(' Month of first observation used in sliding spans ', 'comparison : ',i5,/, ' Year of first observation used in sliding spans ', 'comparison : ',i5)(' Quarter of first observation in first span : ',i5,/, ' Year of first observation in first span : ',i5)(' Quarter of first observation used in sliding spans ', 'comparison : ',i5,/, ' Year of first observation used in sliding spans ', 'comparison : ',i5)(' Name of series being adjusted : ',a8)(' Trading day factors analyzed')(' Seasonally adjusted series with revised yearly totals used in this analysis.')(' Year-to-year changes analyzed',a) for direct and indirect seasonal adjustments. for indirect seasonal adjustments only. for direct seasonal adjustments only..(' regARIMA model coefficients held fixed during ', 'sliding spans analysis.')(' Regressors held fixed during sliding spans analysis:')(' - ',a)Trading DayHolidayUser-defined regressorsOutliers(/,' WARNING: ',a,', fewer than four spans have been used', /,10x,'to compile the measures generated below.',//, 10x,'In this situation, the threshold values used to ', 'determine',/, 10x,'adjustability (15%, 25%, 40%) which appear with ', 'the summary',/, 10x,'tables should be lowered.')By choice of the userDue to the series length(/,' NOTE: Since the trading day coefficients are fixed ', 'in the sliding spans',/, ' analysis, the trading day statistics of the ', 'sliding spans analysis',/,' are not printed.', //,' In addition, the spans statistics for the ', 'seasonally adjusted',/, ' series have the same values as the ', 'corresponding statistics',/, ' for the seasonal factors. In this case, the ', 'statistics for the',/, ' seasonally adjusted series are not printed.',/)(/,' NOTE: Since the holiday coefficients are fixed in ', 'the sliding spans analysis,',/, ' the spans statistics for the seasonally adjusted ', 'series have',/, ' the same values as the corresponding statistics ', 'for the seasonal',/, ' factors. In this case, the statistics for the ', 'seasonally adjusted',/, ' series are not printed.',/)(/,' ERROR: Length of sliding span is too short for ', a,' estimation.', /,' At least five years of data are needed.')trading day and holidaytrading dayholidayQPK T7Y@8(1x,a9,1x, (f8.2,1x,a3),f7.2,1x,f7.2,1x,a3,/)(/,2(7x, (6x,a6),5x,a6,2x,a6,/)) indirect implied adjustment factorsseasonal factors(/,' Summary statistics for mean ',a)(/,21x,'Min',12X,'Max',11X,'Range',/)(4x,'Span ',i1,3(5x,f10.2),/)(2x,'All spans',4x,f10.2,2(5x,f10.2),/)(/,5X,'WARNING: Range of seasonal factors is too low ', 'for summary sliding spans measures to be reliable.', /,14x,'Summary sliding spans statistics not printed out')issranssran(a,a,i2.2,a,1x,a3,3x, (f10.2,2x),f10.2,2x,f10.2).p:(a,'.s',i1,':',3(2x,f10.2))(a,'.all:',3(2x,f10.2))234ssrng.fssx11a.f(/,5x,'Easter adjustment cannot be performed during the ', 'sliding spans analysis',a) due to:.(/,5x,'No years with Easter before April 1st in span ',i1, '.')(/,5x,'No years with Easter after April 16th in span ',i1, '.')(/,5x,'No years with Easter between April 2nd and April ', '8th in span ',i1,'.')(/,5x,'No years with Easter between April 8th and April ', '15th in span ',i1,'.')(/,5x,'Either choose a longer span for the sliding spans ', 'analysis or',/,5x,'preadjust the series using Easter ', 'effects estimated from a',/,5x,'regARIMA model.')NOTE: Since a span is used in the x11regression spec, the irregular regression coefficient estimates will be held fixed during the sliding spans analysis.Pstpitr.f(/,' WARNING: Deviance value increased during ', 'likelihood maximization',/, ' by ',1p,e25.15,' from ',1p,e25.14,'.',/, ' This might indicate a convergence ', 'problem of the successive',/, ' estimates. Print the iterations and ', 'iterationerrors tables',/, ' of the estimate spec to check for ', 'this. If there are convergence',/, ' problems, try specifying initial ', 'values obtained from setting',/, ' exact=none in estimate, or try a ', 'simpler model without parameter',/, ' constraints (See ',a,' of the ',a,').')Section 5Reference Manual?@8??8Y@?Trading Day1-Coefficient Trading DayStock Trading Day1-Coefficient Stock Trading Daysvaict.f(a,/) AICtd : (a:,a)aictest.td: AICtd : noneaictest.td: no(a,': ',e20.10)aictest.diff.tdaictest.cvaic.td AICtd : ARIMA model not aictest.td: nomodelaictest..reg: Length-of-MonthLength-of-QuarterLeap Year AIC : accepted: yes : rejected: noaictest.diff.aictest.cvaic. : ARIMA model not : nomodelaictest.easter.reg: EasterStatCanEasterStockEaster(3x,a,' : ',a,'[',i2,']',/)AICeasteraictest.e: yes(a,i6)aictest.e.window: AICeaster : rejectedaictest.e: noaictest.diff.eaictest.cvaic.e AICeaster : ARIMA model not aictest.e: nomodelUser-defined AICuser : acceptedaictest.u: yes AICuser : rejectedaictest.u: noaictest.diff.u AICuser : ARIMA model not aictest.u: nomodel@parameterparm(1000a)--------- svamcm.fsvchsd.f(a,a,': ',e21.14)chsd.ichsd.Y@svdttm.f('date:',a)('time:',a)svf2f3.f(a,'2.a',i2.2,':',1x,E15.8,10(1X,E15.8))(a,'2.b',i2.2,':',1x,5(2PF8.2),' 100.00',2PF8.2)(a,'2.c',i2.2,':',12(1x,E15.8))(a,'2.d:',4F8.2)(a,'2.e:',12F8.2)(a,'2.mcd:',i8)(a,'2.f:',6F8.2)(a,'2.g:',14F8.2)(a,'2.ic:',F12.2,/,a,'2.is:',F12.2)(a,'2.fsb1:',F11.3,F8.2)(a,'2.fsd8:',F11.3,F8.2,/,a,'2.kw:',F11.3,F8.2,/, a,'2.msf:',F11.3,F8.2)(a,'2.idseasonal: ',a) (indirect adjustment) : (' Moving seasonality ratio ',a,f11.3)(' I/C Ratio ',a,f11.3)(' Stable Seasonal F, D8 table ',a,f11.3)(' Moving Seasonal F, D8 table ',a,f11.3)(' Identifiable seasonality ',a,a) : (' Stable Seasonal F, B1 table ',a,f11.3)(a,'3.m',i2.2,':',1x,f6.3)(' M',i2.2,a,f10.3)(a,'3.q:',1x,F5.2,/,a,'3.qm2:',1x,F5.2,/,a,'3.fail:', 1x,i2)(a,a,f10.3) Q Q2 svflt.f(3a)index---------------------------2 (a)svfltd.f(3a)freq----------------------2 (a)P + svfnrg.f('n',a,': ',i3)(a,i2.2,': ',a)svfreq.f(a,': ',i5)nspecfreq=ntdfreq(a,i1,'.',a,': ',f12.8)tfreq(a,i1,'.',a,': ',i5)indexindex.lowerindex.upper*4$ #).nsfreqs (2<I(1000a)passiooutliermedrmsermset---------------: xotlitr.otlitr.svolit.f??OKsvoudg.f(' ')(' None of the over/under estimation tests for ',a, ' is significant')Variance(' The over/under estimation tests of ',a, ' are significant',/,' for these components:')+++ (' ',a,t40,'(oversmoothing, p value = ',f7.4,')')Trend-Cycle (Full Series)(' ',a,t40,'(undersmoothing, p value = ',f7.4,')')Adjustment (Full Series)Seasonal (Full Series)Irregular (Full Series)Trend-Cycle (Trimmed Series)Adjustment (Trimmed Series)Seasonal (Trimmed Series)Irregular (Trimmed Series)Trend-Cycle (Weighted)Adjustment (Weighted)Seasonal (Weighted)Irregular (Weighted)First Order AutocovarianceSeasonal Order AutocovarianceCrosscovariance(' ',a,t40,'(positive crosscovariance, p value = ', f7.4,')')Seasonal/Irregular(' ',a,t40,'(negative crosscovariance, p value = ', f7.4,')')Seasonal/Trend-CycleTrend-Cycle/Irregular(a,i3)nsigoustatvar: nsigoustat1auto: nsigoustatsauto: nsigoustatcrosscov: (a,2e21.14)oustatvartcfull: oustatvarsafull: oustatvarsffull: oustatvarirfull: oustatvartctrim: oustatvarsatrim: oustatvarsftrim: oustatvarirtrim: oustatvartcwt: oustatvarsawt: oustatvarsfwt: oustatvarirwt: oustat1autotcfull: oustat1autosafull: oustat1autosffull: oustat1autoirfull: oustat1autotctrim: oustat1autosatrim: oustat1autosftrim: oustat1autoirtrim: oustat1autotcwt: oustat1autosawt: oustat1autosfwt: oustat1autoirwt: oustatsautotcfull: oustatsautosafull: oustatsautosffull: oustatsautoirfull: oustatsautotctrim: oustatsautosatrim: oustatsautosftrim: oustatsautoirtrim: oustatsautotcwt: oustatsautosawt: oustatsautosfwt: oustatsautoirwt: oustatccorsfir: oustatccorsftc: oustatccortcir: =(a,'.',a,': ',e20.10)medianrangesvpeak.f>variablevar(100a)--------svrgcm.fsvrvhd.f('history: ',a)yes('historysa: ',a)nofailed(a,10i3)nfctlag: nsalag: nsalags: ntrnlag: ntrnlags: (a,i2,a2,1x,a,',',i4,' to ',i2,a2,1x,a,',',i4)revspan: (a,i4,' to ',i4)period('historytarget: ',a)concurrentfinalsvspan.f(a:,a,a,a,a,a,a:,a,a:,a,a)dateSpanMax_%_DIFF----------------------------- spc rsdorisaindsairrindirr(a,a,i1,a,f9.4).tukey.s: (a,a,f9.4).tukey.td: nonesvtukp.f8؅W4vC(/,' ',a)('a',i2) (2x,i4,3x,3(3(1x,@):,/,9x),3(1x,@),4x,#)(1x,a5,3x,3(3(1x,@):,/,9x),3(1x,@))(2x,i4,4x,3(1x,@):,/,11x,@,35x,#)(1x,a5,4x,3(1x,@):,/,11x,@)(2x,i4,3x,2(4(1x,@):,/,9x),4(1x,@),3x,#)(1x,a5,3x,2(4(1x,@):,/,9x),4(1x,@))(2x,i4,3x,4(1x,@),3x,#)(1x,a5,3x,4(1x,@))(2x,i4,4x,2(4(6x,@):,/,9x),4(6x,@),10x,#)(1x,a5,4x,2(4(6x,@):,/,9x),4(6x,@))(2x,i4,4x,4(6x,@),10x,#)(1x,a5,4x,4(6x,@))(2x,i4,4x,6(1x,@):,/,10x,6(1x,@),4x,#)(1x,a5,4x,6(1x,@):,/,10x,6(1x,@))(2x,i4,4x,6(1x,@):,/,10x,6(1x,@),4x,#)(1x,a5,4x,6(1x,@):,/,10x,6(1x,@))(2x,i4,4x,8(1x,@):,/,10x,4(1x,@),56x,#)(1x,a5,4x,8(1x,@):,/,10x,4(1x,@))(2x,i4,4x,12(1x,@),4x,#)(1x,a5,4x,12(1x,@))(2x,i4,3x,5(2(1x,@):,/,9x),2(1x,@),4x,#)(1x,a5,3x,5(2(1x,@):,/,9x),2(1x,@)))(2x,i4,3x,2(1x,@):,/,9x,2(1x,@),4x,#)(1x,a5,3x,2(1x,@):,/,9x,2(1x,@))<-(a) Year ('f',i2,'.',i1)(' ')XXXXXforecasts of (prior adjusted) original seriesregARIMA outlier componentregARIMA temporary change outlier componentregARIMA temporary change outlier componentregARIMA trading day component forecastsregARIMA holiday component forecastsregARIMA user-defined regression component forecastsregARIMA seasonal component forecastsregARIMA transitory component forecastsfinal seasonal component forecastsfinal seasonal component forecastsfinal seasonal difference forecastsfinal seasonal component forecasts, adjusted for regARIMA seasonal componentseasonal factors forecasts, before shrinkage appliedX-11 Easter adjustment factor forecastscombined holiday component forecastscombined adjustment component forecastscombined adjustment component forecastsfinal adjustment difference forecastscombined calendar adjustment component forecastsfinal adjustment ratio forecaststotal adjustment factor forecastsforecasted factors applied to get adjusted series with forced yearly totalsprior trading day component forecastsfinal irregular component regression trading day component forecastsfinal irregular component regression trading day component forecastsfinal irregular component regression holiday component forecastsfinal irregular component regression calendar component forecastsfinal irregular component regression combined calendar component forecastsforecasts of (prior adjusted) original seriesfinal indirect seasonal component forecastsfinal indirect seasonal component forecastsindirect final seasonal difference forecastsfinal indirect adjustment ratio forecastsindirect total adjustment factor forecastsfinal indirect calendar component forecastsfinal indirect adjustment component forecastsfinal indirect adjustment component forecastsforecasted factors applied to get indirect adjusted series with forced yearly totalsFinal trend component forecast (SEATS)Final trend component forecast with constant added (SEATS)Final seasonal component forecast (SEATS)Final seasonal component forecast (SEATS)Final irregular component forecast (SEATS)Final irregular component forecast (SEATS)Final seasonally adjusted series forecast (SEATS)Final seasonally adjusted series forecast with constant added (SEATS)Final transitory component forecast (SEATS)Final transitory component forecast (SEATS)Final combined adjustment factor forecast (SEATS)Final combined adjustment factor forecast (SEATS)final adjustment ratio forecasts (SEATS)total adjustment factor forecasts (SEATS)Final differenced forecast after transformation, prior adjustment (SEATS)Final differenced seasonally adjusted series forecast (SEATS)Final differenced trend forecast (SEATS)Final seasonal component forecast (SEATS)final cycle forecastfinal long term trend forecastFinal seasonally adjusted series forecast adjusted for outliers (SEATS)Final irregular component forecast outlier adjusted (SEATS)(' First pass - Estimating ',a)irregular regression and X-11 Easter effectsirregular regression effectsX-11 Easter effectstable.f@??PERT!@tblhdr.f(' First pass - Estimating ',a)irregular regression and X-11 Easter effectsirregular regression effectsX-11 Easter effects8(' Prior daily weights Mon Tue Wed ', 'Thur Fri Sat Sun',/,19X,7F8.3)(' Daily weights Mon Tue Wed Thur ', 'Fri Sat Sun',/,13X,7F8.3)(' Combined daily weights Mon Tue Wed ', 'Thur Fri Sat Sun',/,22X,7F8.3)(' Trend filter Centered ',i3,'-term moving average')(' Trend filter ',i3,'-term Henderson moving average',/, ' I/C ratio ',F6.2)(' Seasonal filter Different moving averages used ', 'for each ',a)(' Seasonal filter ',a,' moving average')(' ',a,' shrinkage technique applied to seasonal.')GlobalLocal(' Includes ',i2,' backcasts.')(' Irregular component regression sigma limit ',f5.2)(' Lower sigma limit ',f5.2,/,' Upper sigma limit ', f5.2)(' ',a,' outliers removed')AO & TCAOTC(' Denton method used.')(' Regression method used, with lambda = ',f10.7, ', rho = ',f10.7,'.')(' Temporary prior adjustments included.')(' Type of revision: Percent')(' Type of revision: Difference')(' ',a,'easonally adjusted series ',a, 'sed in this analysis.')Rounded swith revised yearly totals uusRounded indirect sIndirect s(' MCD filter ',i1,' x ',i1,' moving average')montuewedthufrisatV@p>@?Trading DayStock Trading Day1-Coefficient Trading Day1-Coefficient Stock Trading Day ('(1x,a,t',i2,',a,1x,f15.4)')(a,1x,i6)aictest.td.num:(a,1x,a)aictest.td.reg:aictest.td.reg2:Length-of-Stock Length-of-Leap YearLength-of-Month8Length-of-Quarter(//,' Likelihood statistics for model ',a,' ',a)withoutwithAICC(no td):('aictest.td.aicc.',a,': ',e29.15)notdAICC()(//,' ***** AICC (with aicdiff=',F7.4, ') prefers model ',a,' ',a,' *****')LPYtdaic.fTrading DayTrading Day + Leap Year + Length of Quarter + Length of Month (Combined Trading Day RegressorsCombined Trading Day and Leap Year and Length of Quarter and Length of Month RegressorsUser-defined Trading Day tdftest.f(' ',120(a))- 88lstempls.f(a,i5)lsrun: nlsrun: ('(/,'' '',a,/,'' '',a,t',i2, ',a,'' '',a, /,'' '',',i3, '(''-''))')Tests for Cancellation of Level ShiftsDates of LS SetsSpant-value('(2x,a,t',i2,',i5,f8.2)')+('lsspan',i2.2,': ',a,a,i3,a,e21.14) n ERROR: Data too large for X-13ARIMA-SEATS print format. Try dividing the series by power of 10, or use the divpower argument found in the series and composite specs.tfmts.f('f',i2,'.',i1)('f',i1,'.',i1)(2x,i4,3x,3(3(1x,@):,/,9x),3(1x,@),4x,#)(1x,a5,3x,3(3(1x,@):,/,9x),3(1x,@))(2x,i4,4x,3(1x,@):,/,11x,@,35x,#)(1x,a5,4x,3(1x,@):,/,11x,@)(2x,i4,3x,2(4(1x,@):,/,9x),4(1x,@),3x,#)(1x,a5,3x,2(4(1x,@):,/,9x),4(1x,@))(2x,i4,3x,4(1x,@),3x,#)(1x,a5,3x,4(1x,@))(2x,i4,4x,2(4(6x,@):,/,9x),4(6x,@),10x,#)(1x,a5,4x,2(4(6x,@):,/,9x),4(6x,@))(2x,i4,4x,4(6x,@),10x,#)(1x,a5,4x,4(6x,@))(2x,i4,4x,6(1x,@):,/,10x,6(1x,@),4x,#)(1x,a5,4x,6(1x,@):,/,10x,6(1x,@))(2x,i4,4x,6(1x,@):,/,10x,6(1x,@),4x,#)(1x,a5,4x,6(1x,@):,/,10x,6(1x,@))(2x,i4,4x,8(1x,@):,/,10x,4(1x,@),56x,#)(1x,a5,4x,8(1x,@):,/,10x,4(1x,@))(2x,i4,4x,12(1x,@),4x,#)(1x,a5,4x,12(1x,@))(2x,i4,3x,5(2(1x,@):,/,9x),2(1x,@),4x,#)(1x,a5,3x,5(2(1x,@):,/,9x),2(1x,@)))(2x,i4,3x,2(1x,@):,/,9x,2(1x,@),4x,#)(1x,a5,3x,2(1x,@):,/,9x,2(1x,@))('a',i2)('a',i1)tfmts3.f('(/,15x,''Table Total- '',f',a,'.',i1,',8x,''Mean- '',f', a,'.',i1,',8x,''Std. Deviation- '',f',a,'.',i1,',/,',i2, 'x,''Min - '',f',a,'.',i1,',18x,''Max - '',f',a,'.',i1,')')('(/, 2x,''Table Total- '',f',a,'.',i1,',3x,''Mean- '',f', a,'.',i1,',3x,''Std. Dev.- '',f',a,'.',i1,',/,',i2, 'x,''Min - '',f',a,'.',i1,',8x,''Max - '',f',a,'.',i1,')')8?transc.f(/,' CUBIC ITERATIONS EXCEEDED')?@?@"@;@;-C6 ??& .>?{Gz?Gz??(/,' ERROR: Unable to set up ARIMA model for automatic ', 'transformation selection',/, ' procedure for the reason(s) given above.')(/,' Estimation error found during automatic ', 'transformation selection', /,' procedure while fitting regARIMA model to the ',a, ' series.')untransformed(//, ' Likelihood statistics for model fit to untransformed series.')(' AICC(no log) : ',f15.4)('aictest.trans.aicc.',a,': ',e29.15)nologlog transformed(//, ' Likelihood statistics for model fit to log transformed series.')(' AICC(log) : ',f15.4)log(//,' ***** AICC (with aicdiff=',F5.2, ') prefers log transformation *****')(' ***** Multiplicative seasonal adjustment will be performed. ****')(//)(/,' Automatic transformation test : ',a)Log TransformationMultiplicative Seasonal AdjustmentLPYLOMLOQpercent change ratios NOTE: At least one value that is either less than or equal to zero or equal to the missing value code was found after the span of data to be analyzed, but within the time frame of the forecasts generated by the regARIMA model. In this situation, the forecast output will not include a comparison of the transformed forecasts with the corresponding values of the transformed original series.(//,' ***** AICC (with aicdiff=',F5.2, ') prefers no transformation *****')(' ***** Additive seasonal adjustment will be performed. ****')No TransformationAdditive Seasonal Adjustment comparison of the forecasts with the corresponding values of the original series.Leap Year8('finmode: ',a)multiplicativeadditivetrnaic.ftrnfcn.f(/,' ERROR: Cannot ',a,' a proportion not in the range ', '(0,1), y(',i5,')=',1p,g16.8,'.',/)take the logit of(' ERROR: Maximum number of errors printed. More errors ', 'may exist, but',/, ' will not be specified. The above values ', 'cannot be processed.')?(' ERROR: Do not take ',a,', y(',i5,')=',1p,g16.8,'.')log of a negative numberlog of zerolog of a zeroBoxCox transform?@tstmd1.f(' ',a) Due to insignifcant ARMA coefficients, model changed to(' ',2(' (',i2,',',i2,',',i2,')'))? Model changed to default model Mean is signficant.Constant8(' WARNING: A significant mean term will not be added ', 'to the model since',/, ' the automdl argument checkmu was set to ', 'no in the input',/, ' specification file.')\(\?ffffff??= ףp=??usraic.f(//,' Likelihood statistics for model with user-defined', ' regressors')8(' AICC(userreg) : ',f15.4)('aictest.u.aicc.',a,': ',e29.15)user045User-defined(//,' Likelihood statistics for model without user-defined', ' regressors')(' AICC(no userreg) : ',f15.4)nouser(//,' ***** AICC (with aicdiff=',F7.4, ') prefers model ',a,' user-defined regressor *****')with1User-defined Holiday2User-defined Holiday Group 23User-defined Holiday Group 3User-defined Holiday Group 4User-defined Holiday Group 5&User-defined Seasonalwithout?@?Y@8@ &@@;@@ffffff?333333?@1@"@N@@.@*@ @Q?(\?(@? @wr.f( ///,2x,'SERIES | # OF OBS. | # OF | TYPE OF |', ' OUTLIERS |',/,2x, ' | | OBS/YEAR | ADJUSTMENT |', ' LEVEL SHIFT | ',A,' |')( 2x,'--------|-----------|----------|------------|', '-------------|------------|')(10x,'|',11x,'|',10x,'|',12x,'|',13x,'|',12x,'|')(2x,a8,'|',4x,i3,4x,'|',4x,i2,4x,'|',5x,a1,6x,'|')19-JUL-2001writln.f(' ',a) 8wrtmss.f-('(1X,I2,A1,I4,2X,',i1,'(A10,1X),3X,A9,2x,a10)')('(1X,I2,A1,I4,2X,',i1,'(A9,2X),3X,A9,2x,a10)')('(1X,I2,A1,I4,2X,E10.4,1X,',i1,'(A10,1X),3X,A9,2x,a10)')('(1X,I2,A1,I4,2X,F9.2,2X,',i1,'(A9,2X),3X,A9,2x,a10)')('(1X,I2,A1,I4,2X,',i1,'(A10,1X),E10.4,1X,3X,A9,2x,a10)')('(1X,I2,A1,I4,2X,',i1,'(A9,2X),F9.2,2X,3X,A9,2x,a10)')('(1X,I2,A1,I4,2X,',i1,'(E10.4,1X),',i1, '(A10,1X),3X,F9.2,2x,a10)')('(1X,I2,A1,I4,2X,',i1,'(F9.2,2X),',i1, '(A9,2X),3X,F9.2,2x,a10)')('(1X,I2,A1,I4,2X,',i1,'(A10,1X),',i1, '(E10.4,1X),3X,F9.2,2x,a10)')('(1X,I2,A1,I4,2X,',i1,'(A9,2X),',i1, '(F9.2,2X),3X,F9.2,2x,a10)') wrtotl.f(/,' ERROR: Invalid outlier type,',i5,', ',a,'.')8?wrttb2.f('(',i1,'x,f',i1,'.',i1,',a)')('(',i1,'x,f',i2,'.',i1,',a)')('(f',i1,'.',i1,',a)')('(f',i2,'.',i1,',a)')XXXXX ('( f',i2,'.',i1,')')(a)؅W4vCY@?{Gz?8?wrttbl.f('(',i1,'x,f',i1,'.',i1,')')('(',i1,'x,f',i2,'.',i1,')')XXXXX ('( f',i2,'.',i1,')')(a)؅W4vCY@?{Gz? Trading DayStock Trading DayLeap Year8x11aic.f(//,'AICC for model without ',a,t50,f20.4,/, 'AICC for model with ',a,t50,f20.4)('(1x,a,t',i2,',a,1x,f15.4)')AICC(no td):AICC()('aictest.xtd.aicc.',a,': ',e29.15)notdtd('aictest.xtd.reg: ',a)(//,' ***** AICC (with aicdiff=',F5.2,') prefers ', 'model ',a,' *****')with without EasterStatCanEaster(//,' AICC for model without Easter',t50,f20.4)(' AICC(no easter) : ',f15.4)('aictest.xe.aicc.',a,': ',e29.15)noeaster(' AICC for model with ',a,'[',i2,']',t50,f20.4)(' AICC(',a,'[',i2,']) : ',f15.4)eastersceaster('aictest.xe.aicc.',a,i2.2,': ',e29.15)(//,' ***** AICC (with aicdiff=',F5.2, ') prefers model without Easter *****')(//,' ***** AICC (with aicdiff=',F5.2, ') prefers model with ',a,'[',i2,'] *****')Statistics Canada EasterThanksgivingLabor(//,' AICC for model without user-defined regressors',t50, f20.4)(' AICC(',a,') : ',f15.4)no userreg('aictest.xu.aicc.',a,': ',e29.15)nouserUser-defined(' AICC for model with user-defined regressor(s)',t50, f20.4)userreguserwith user-defined regressor(s)without user-defined regressor(s)The program will not estimate a regARIMA model for a constant series.(a,e15.8)barima:barima.diag:earima:earima.diag:NOTE: The program will only generate an X-11 seasonal adjustment for monthly or quarterly series.bx11:bx11.diag: bseats:bseats.diag:eseats:eseats.diag:ex11:ex11.diag:bspectrum:espectrum:NOTE: The program will only generate a SEATS adjustment for monthly, bimonthly, quarterly, biannual or annual.x11ari.fVDK  EasterStatCanEasterStock Trading DayTrading DayP8Leap Yearprior trading day factorsextreme irregular values excluded from irregular component regressionextreme irregular values excluded from irregular component regressionpreliminary irregular component regressionfinal irregular component regressionpreliminary trading day factors from irregular component regressionfinal trading day factors from irregular component regressionpreliminary combined trading day factors from irregular component regressionfinal combined trading day factors from irregular component regressionpreliminary holiday factors from irregular component regressionfinal holiday factors from irregular component regressionpreliminary calendar factors from irregular component regressionfinal calendar factors from irregular component regressionpreliminary combined calendar factors from irregular component regressionfinal combined calendar factors from irregular component regressionAO outlier detection results for irregular component regression, by iterationregression matrix used in final irregular component regressioncovariance matrix of irregular component regression parameter estimatesresults of AIC tests used in final irregular component regression(/,' ',a)Irregular Regression ModelExtreme Value Adjustment Method(' Exclude irregular values outside ',f5.2,' sigma limit')(' Automatic AO outlier identification')(a) AICtdX : acceptedaictest.xtd: yes AICtdX : rejectedaictest.xtd: no AICeasterX : acceptedaictest.xe: yes(a,i3)aictest.xe.window: AICeasterX : rejectedaictest.xe: noaictest.xe.window: 0User-defined AICuserX : acceptedaictest.xu: yes AICuserX : rejectedaictest.xu: no(' NOTE: Because of the AIC test result, ',a,' ', 'has removed any trading day,',/,7x, 'stock trading day, or holiday regressors from the ', 'irregular component',/,7x, 'regression model. No further model estimation will ', 'be attempted.',//)X-13ARIMA-SEATS?nfinalxreg: 1(' Mon Tue Wed Thur Fri', ' Sat Sun(*)',/,3X,7F9.4,//)finalxreg01: none*Irregular Component Regression Matrix(a,7(1x,f15.7))x11tdwt:(' ERROR: Cannot generate factor necessary to ', 'reweight trading day',/, ' daily weights - none of the unfixed daily ', 'weights are greater',/,' than zero.')x11tdwt2:(' NOTE: At least one of the parameter estimates ', 'above yields a negative',/, ' daily weight for the ',a,' 16 table. The ', 'reweighting done to avoid',/, ' negative daily weights in Table ',a,' 16 ', 'produced the following',/, ' parameter estimates, which were used to ', 'obtain the ',a,/, ' trading day factors of ',a,' 16:',/)BpreliminaryCfinal(' Weekday Weekend(**)',/,3X,2(3x,F8.4),//)(' ERROR: At least one of the stock trading day ', 'regression coefficient',/, ' estimates from the irregular regression ', 'model produce',/, ' nonpositive trading day factors for ', 'multiplicative seasonal',/,' adjustments.',//, ' Use the regression spec to estimate the ', 'stock trading day effect.',//)x11combtdwt:finalxregx11mdl.f@x11plt.f (LSrampoutliers included) (AO & TC outliers included) (AO outliers included) (TC outliers included) (also adjusted for trading day holiday AO, TC & LS outlier TC & LS outlier TC & AO outlier TC outlier AO outlier user-defined effects AO & LS outlier LS outlier8Data for regARIMA modelingData Original Series with Constant Added Prior Adjusted Series (Before Prior Calendar Adjustments)Prior Adjusted Series (Permanent Prior Factors)Prior Adjusted Series? lom loq lpyear temp perm('prioradj:',a) none  !(/,' ERROR: Initial seasonal factor is equal to ', 'zero - cannot continue with', /,' pseudo-additive seasonal adjustment.',/) ('calendarsigma.',i2.2,': ',f10.2)x11pt2.f ?? (2i5)(1x,e21.14)('finaltrendma: ',i3) 8 NOTE: Negative values were created in the seasonally adjusted series when removing the temporary constant. Negative values in the seasonally adjusted series were replaced by zero before forcing annual totals.NOTE: Values <= 0 were found in the forced seasonally adjusted series. These values were corrected by replacing the negative values with zero and prorating the modified forced seasonallyadjusted series with the target series. These values were corrected by replacing the negative values with zero.NOTE: Values <= 0 were found in the final forced seasonally adjusted series. Forcing factors for these observations were set to -999. x11pt3.f-t.y/{810e532e654e6a76e6r98e7;:e8  <=>NOTE: Seasonal adjustment diagnostics cannot be generated because the series listed below have either a variance of zero or a variance could not be computed: - the original series adjusted for extreme values. - the irregular component. - the trend component. - the original series adjusted for regARIMA outlier and user-defined regression effects. - the original series adjusted for regARIMA outlier effects. - the original series adjusted for user-defined regression effects. - the original series. - the original series with the linear trend removed.?uiffJKI8?? X-13ARIMA-SEATS run of X-13ARIMA-SEATS('version: ',a,/,'build: ',a,/,'output: out')1.126(a,'U. S. Department of Commerce, U. S. Census Bureau')(/,a)1(a,a,1x,a,1x,a,' Method,')(a,a,1x,a,' Method,')(a,'Release Version ',a,' Build ',a)(/)(a,'This software application provides an enhanced ', 'version of',/, a,'Statistics Canada''s X-11-ARIMA extension (Dagum, ', '1980)',/, a,'of the X-11 variant of the Census Method II of',/, a,'Shiskin, Young and Musgrave (1967).',// a,'It also provides an ARIMA model-based method ', 'following',/, a,'Hillmer and Tiao (1982) and Burman (1980) that is ', 'very similar',/, a,'to the update of the method of SEATS (Gomez and ', 'Maravall, 1996)',/, a,'produced at the Bank of Spain by G. Caporello and',/, a,'A. Maravall for TSW (Caporello and Maravall, 2004).',/, a,'The present application includes additional ', 'enhancements.',//, a,a,' includes an automatic ARIMA model selection ', 'procedure',/, a,'based largely on the procedure of Gomez and Maravall ', '(1998)',/, a,'as implemented in TRAMO (1996) and subsequent ', 'revisions.',//, a,'Primary Programmers: Brian Monsell, Mark Otto and,',/, a,'for the ARIMA model-based signal extraction,',/, a,'Gianluca Caporello and Victor Gomez',//)(5x,'Series Title- ',a)(5x,'Series Name- ',a) (5x,a)(24x,a)(/,a,'-Period covered- ',i2,a2,1x,a,',',i4,' to ',i2,a2, 1x,a,',',i4)(/,a,'-Period covered- ',i4,' to ',i4)(/,a,'-Period covered- ',i4,'.',i2.2,' to ',i4,'.',i2.2)(a,'-Type of run - ',a,1x,a)()(a,'-Sigma limits for graduating extreme values are ', f4.1,' and ',f4.1,' .')(a,'-The following moving averages were selected for ', 'the seasonal factor curves:')(a,4(1x,a3,1x),/,a,4(1x,a4))(a,12(1x,a3,1x),/,a,12(1x,a4))(a,'-3x3 moving average used in section 1 of each ', 'iteration,',/,a,'3x5 moving average in section 2 of ', 'each iteration.')(a,'-3x3 moving average used in section 1 of each ', 'iteration, ',/,a,'3x5 moving average in section 2', ' of iterations B and C,'/,a, 'moving average for final seasonal factors chosen by ', 'Global MSR.')(a,'-a ',a,' moving average selected for the ', 'seasonal factor curves.')(a,'-Moving average for the variable trend cycle ', 'routine is a ',i3,'-term Henderson')(a,' adjustment')adjustment(a,'-Prior ',a,' ',a,' factors.')(temporary and permanent)(temporary)(permanent)8(a,'-Constant value added to series (',a,')')(a,'-Prior trading day adjustment.')Trading day and holidayTrading dayStock trading dayHoliday(a,'-',a,' irregular regression computed ', 'starting ',a,' with AO outliers identified using', ' a',/,a,'critical value of ',f5.2,'.')(a,'-',a,' irregular regression computed ', 'starting ',a,/,a,' with AO outliers identified ', 'using a critical value of ',f5.2,'.')(a,'-',a,' irregular regression computed ', 'starting ',a,' with AO outliers identified using', ' a',/,a,'default critical value.')(a,'-',a,' irregular regression computed ', 'starting ',a,/,a,' with AO outliers identified ', 'using a default critical value.')(a,'-',a,' irregular regression computed ', 'starting ',a,' excluding irregular values outside ', f5.2,'-sigma limits.')(a,'-',a,' irregular regression computed ', 'starting ',a,/,a,' excluding irregular values ', 'outside ',f5.2,'-sigma limits.')(a,'-',a,' irregular regression computed ', 'starting ',a)(a,'-',a,' irregular regression estimates',a,'applied',a) as prior factors.. notStock Trading daystock trading daytrading dayEasteruser-defined(a,'-Irregular regression AIC test performed for ',a, ' regressors.')(a,'-Prior holiday adjustment factors estimated ', 'for:')(a,'- Easter')(a,'-Permanent prior adjustment factors will be applied', ' directly to the final seasonally adjusted series')(a,'-Holiday adjustment factors applied directly to the ', 'final seasonally adjusted series')(a,'-Sliding spans analysis performed')(a,'-Spectral estimates of original series, table ', 'D11 and table E3 will be searched for ',/,a, 'signficant seasonal and trading day peaks')(a,'-Spectral plots generated with rho for Tukey-', 'Hanning taper = ',f6.3)(a,'-Spectral plots generated for selected series')(a,'-Spectral plots generated for series starting in ',a)(a,'-X-11 outlier detection procedure uses moving median', ' absolute deviations')(a,'-X-11 outlier detection procedure uses moving median', ' absolute deviations of the log data')(a,'-X-11 outlier detection procedure uses tau ', 'adjustment to moving median absolute deviations')(a,'-X-11 outlier detection procedure uses tau ', 'adjustment to moving median absolute deviations of ', 'the log data')(a,'-X-11 seasonal factors adjusted using ',a, 'shrinkage factors from Miller and Williams (2003)')globallocal(a,'-Spectral estimates of original series will be ', 'searched for signficant trading day peaks')(a,'-Spectral plot of the original series will be ', 'generated with rho for Tukey-Hanning taper = ',f6.3)(a,'-Spectral plot of the original series generated')(a,'-SEATS model based seasonal adjustment performed.')(a,'-Modify the D11. series to make the yearly totals ', 'of the seasonally')(14x,'adjusted series agree with the original series.')(14x,'adjusted series agree with the calendar adjusted', ' series.')(14x,'adjusted series agree with the permanent prior ', 'adjusted',/,14x,'series.')(14x,'adjusted series agree with the calendar and ', 'permanent prior',/,14x,'adjusted series.')(a,'-Denton method used.')(a,'-Regression method used, with lambda = ',f10.7, ', rho = ',f10.7,'.')(a,'-First ',a,' of fiscal year set to be ',a,a) Quarter(a,'-Printout suppressed. Only user-specified tables and', ' plots will be printed out.')(//,' Tables labeled "First pass" are from an initial', ' seasonal adjustment used to estimate ',/, ' irregular regression and/or X-11 Easter effects.')(//,' All values of original series divided by 10 ** ', i2,' in this run.')(a,': ',a)srstitsrsnam(a,': ',i5)freq('span: ',i2,a2,1x,a,',',i4,' to ',i2,a2,1x,a,',',i4)('span: ',i4,' to ',i4)perioddatatypeflowstock(a,': ',e20.10)constantnfcst(a,': ',f12.6)ciproblognormalyesnomvvaliqtypeljungboxboxpierce(a,': ',a,1x,a)samode(a,':',2(1x,f12.6))siglimadjtotadjtotstartadjtottargetoriginalpprioradjbothadjtottyperegressionadjtotlambdaadjtotrhoadjtotmoderatiodiffadjtotfctdentonseasonalmaNone(a,': ',11(a4,2x),a4)trendmadefaultpriortdx11regressx11regressextremeautoaox11irrcrtvalsigmax11irrsiglimnonex11easterx11otlstderrmadmadlogtaumadtaumadlogshrinkdivpowerspectrum('startspec: ',i2,a2,1x,a,',',i4)spectypeAR-spectrumperiodogramdecibelspecseriesoutlieradjoriginaladjoriginalmodoriginalspecmaxaraltfreqshowseasonalfreqsaveallspecfreqpeaklocalpeakwdsiglevelcomptypeaddsubmultdivcompwtmetadata.x12hdr.fx12run.f error in genfor - unable to open input/output files for X-13ARIMA-SEATSERROR: Error(s) were found while executing the spec file(s) of component series used for this composite adjustment. The direct and indirect seasonal adjustment of the total series will not be performed. Correct the error(s) for the component series and rerun the metafile . **Correct input and rerun .spc** Input checking complete for .spc('mdg: ',a)yesno8(a,e15.8)bx12run:bx11ari:ex11ari:('history: ',a)('sspans: ',a)('historysa: ',a)bsspan:failed(/,' Sliding spans analysis failed : check error file.')esspan:bhist:60(/,' History analysis failed : check error file.')ehist:ex12run:8Y@045???V8?nComp pass the MaxComp components #B ;??@?@i@`!@OK ( '(p=', f6.3, ')' )+ - ++--(////, 2x,'SECOND ORDER MOMENTS OF THE (STATIONARY)', ' COMPONENTS ', 'OVER / UNDER ESTIMATION TESTS',/,2x, 81('-'))(//,4x,'1. VARIANCE',/,4x,11('-'),/)( 6x, a, 4x, ( 2x, a, 2x, a ) )TREND-CYCLE (Full) TREND-CYCLE (Noend) TREND-CYCLE (Weighted)??SEASONAL (Full) SEASONAL (Noend) SEASONAL (Weighted) IRREGULAR (Full) IRREGULAR (Noend) IRREGULAR (Weighted) ADJUSTED (Full) ADJUSTED (Noend) ADJUSTED (Weighted) (//,4x,' ++ : Overestimation of component.', ' Strong evidence (p<.0013).')(4x,' + : Overestimation of component.', ' Mild evidence (.0013?_LU???Invalid value for record markerShort record on unformatted readFile already opened in another unitCorrupt unformatted sequential fileInternal error in run-time libraryWrite exceeds length of DIRECT access record../../../libgfortran/runtime/error.clen >= (sizeof (GFC_UINTEGER_16) * 2 + 1)len >= (sizeof (GFC_INTEGER_16) * 3 + 2)Operating system error: %s %s Unknown error codeEnd of recordEnd of fileSuccessful returnOperating system errorBad statement optionMissing statement optionConflicting statement optionsUnattached unitFORMAT errorIncorrect ACTION specifiedRead past ENDFILE recordBad value during readNumeric overflow on readInternal unit I/O errorFortran runtime error: %s Fortran runtime warning: %s At line %d of file %s Internal Error: %s Wjh]jhcjhijhojhujh{jhjhjhjhjhjhjhjhjhjhjhQjhjhjhxtoagfc_itoaUnable to determine machine endiannessInternal: NULL mem pointer in DEALLOCATE.Internal: Attempt to DEALLOCATE unallocated memory.Internal: NULL mem pointer in ALLOCATE.ALLOCATE64: Attempt to allocate negative amount of memory. Possible integer overflowAttempt to allocate negative amount of memory. Possible integer overflowAttempting to allocate already allocated array.Attempt to allocate a negative amount of memory.ALLOCATE: Out of memory.Memory allocation failedSTOP %cSTOP %d Bad STATUS parameter in CLOSE statementCan't KEEP a scratch file on CLOSEkeepdeleteZxZxSpecified UNIT in FLUSH is not connectedCannot REWIND a file opened for DIRECT accessIllegal value for record markerSEQUENTIALDIRECTNOUNFORMATTEDinquire_via_unit(): Bad formNULLZEROinquire_via_unit(): Bad blankAPPENDASISREWINDREADWRITEQUOTEAPOSTROPHENONEinquire_via_unit(): Bad delimYESinquire_via_unit(): Bad padBIG_ENDIANLITTLE_ENDIANinquire_via_unit(): Bad accessinquire_via_unit(): Bad actioninquire_via_unit(): Bad convertUNDEFINEDDELIM parameter conflicts with UNFORMATTED form in OPEN statementBLANK parameter conflicts with UNFORMATTED form in OPEN statementPAD paramter conflicts with UNFORMATTED form in OPEN statementACCESS parameter conflicts with SEQUENTIAL access in OPEN statementMissing RECL parameter in OPEN statementRECL parameter is non-positive in OPEN statementFILE parameter must not be present in OPEN statementCannot change STATUS parameter in OPEN statementCannot change ACCESS parameter in OPEN statementCannot change FORM parameter in OPEN statementCannot change RECL parameter in OPEN statementCannot change ACTION parameter in OPEN statementOPEN statement must have a STATUS of OLD or UNKNOWNBad ACCESS parameter in OPEN statementBad ACTION parameter in OPEN statementBad BLANK parameter in OPEN statementBad DELIM parameter in OPEN statementBad PAD parameter in OPEN statementBad FORM parameter in OPEN statementBad POSITION parameter in OPEN statementBad STATUS parameter in OPEN statementBad CONVERT parameter in OPEN statementBad unit number in OPEN statementCannot use POSITION with direct access filesConflicting ACCESS and POSITION flags in OPEN statementExtension: APPEND as a value for ACCESS in OPEN statementError closing file in OPEN statementfort.%dnew_unit(): Bad statusUnit number changedIllegal value for CONVERTsequentialdirectappendreadwritezerononeapostrophequoteyesnounformattedasisrewindunknownoldnewreplacescratchnativeswapbig_endianlittle_endianbxbxbxSWxnxbxo{bxbxbxbxbxbxcxbx cxcxbxcxcx#cx'cx/cx7cx>cxCcxNcxDerived type I/O should have been handled via the frontend.Expected %s for item %d in formatted transfer, got %sComma in formatted numeric read.Insufficient data descriptors in format after reversionformatted_transfer(): Bad typeConstant string in input formatCannot read from file opened for WRITECannot write to file opened for READFormat present for UNFORMATTED data transferA format cannot be specified with a namelistMissing format for FORMATTED data transferInternal file cannot be accessed by UNFORMATTED data transferDirect access data transfer requires record numberRecord number not allowed for sequential access data transferBad ADVANCE parameter in data transfer statementADVANCE specification conflicts with sequential accessADVANCE specification conflicts with internal fileADVANCE specification requires an explicit formatEOR specification requires an ADVANCE specification of NOSIZE specification requires an ADVANCE specification of NOEND specification cannot appear in a write statementEOR specification cannot appear in a write statementSIZE specification cannot appear in a write statementRecord number must be positiveCannot READ after a nonadvancing WRITEtransfer_array(): Bad typeINTEGERLOGICALCHARACTERREALtype_name(): Bad typeCOMPLEXBad format nodeRecord number too largeNon-existing record numberhܠhѠhƠhhhhhh=h6h/h(hhh@hQhhQhhhhSh?hgh{hhhμhhhh˺hhhTh0hh9h{hhhbxbxinsert(): Duplicate key found!GFORTRAN_TMPDIRTMPTEMP/tmp%s/gfortrantmpXXXXXXregular_file(): Bad actionregular_file(): Bad statusopen_external(): Bad action*len >= 0hHhhhhNOYESUNKNOWNmem_alloc_w_at../../../libgfortran/io/unix.c A?bad integer kindUnspecified precision%+-#31.*Leprintf is brokenUnexpected format token%+0*dbad real kind %d*(,Bad type for namelist write& / h h+hhChhhhVhhhhhhhhjhh hhhhhhhhhhhhhhhh"iLii)ihhhLiXiiiiiiiPiiigi iiotoabtoa?list_formatted_write(): Bad type../../../libgfortran/io/write.clen >= (sizeof (GFC_INTEGER_16) * 8 + 1)len >= (sizeof (GFC_INTEGER_16) * 3 + 1)Missing argument to get_command_argument75ư>../../../libgfortran/intrinsics/date_and_time.clen >= 3%04d%02d%02d%02d%02d%02d.%03d%+03d%02d__zone_len >= 5__time_len >= 10__date_len >= 8 @N@idate_i8idate_i4itime_i8itime_i4date_and_timeAugument NCOPIES is negative./_?;Array rank of PUT is not 1.Array rank of GET is not 1.Array size of PUT is too small.Array size of GET is too small.[U;]h:Vɹ"MSGNU Fortran 95 runtime library version UNKNOWN --help Print this list Unit number that will be preconnected to standard input (No preconnection if negative)Unit number that will be preconnected to standard output (No preconnection if negative)Unit number that will be preconnected to standard error (No preconnection if negative)Sends library output to standard error instead of standard output.Directory for scratch files. Overrides the TMP environment variable If TMP is not set /tmp is used.If TRUE, all output is unbuffered. This will slow down large writes but can be useful for forcing data to be displayed immediately.If TRUE, print filename and line number where runtime errors happen.Print optional plus signs in numbers where permitted. Default FALSE.Default maximum record length for sequential files. Most useful for adjusting line length of preconnected units. Default 1073741824Separatator to use when writing list output. May contain any number of spaces and at most one comma. Default is a single space.How to initialize allocated memory. Default value is NONE for no initialization (faster), NAN for a Not-a-Number with the mantissa 0x40f95 or a custom hexadecimal valueWhether memory still allocated will be reported when the program ends.Whether the program will IGNORE or ABORT on SIGHUP.Whether the program will IGNORE or ABORT on SIGINT.Set floating point rounding. Values are NEAREST, UP, DOWN, ZERO.Precision of intermediate results. Values are 24, 53 and 64.Set format for unformatted filesEnvironment variables: ---------------------- Integer Boolean String Runtime error codes: -------------------- %d %s Command line arguments: DefaultBad Set %s (Unknown) %s "%s" 0x%xYesNo%s %s %s %d NaNGFORTRAN_UNBUFFERED_%dGFORTRAN_STDIN_UNITGFORTRAN_STDOUT_UNITGFORTRAN_STDERR_UNITGFORTRAN_USE_STDERRGFORTRAN_UNBUFFERED_ALLGFORTRAN_SHOW_LOCUSGFORTRAN_OPTIONAL_PLUSGFORTRAN_DEFAULT_RECLGFORTRAN_LIST_SEPARATORGFORTRAN_MEM_INITGFORTRAN_MEM_CHECKGFORTRAN_SIGHUPGFORTRAN_SIGINTGFORTRAN_FPU_ROUNDGFORTRAN_FPU_PRECISIONGFORTRAN_CONVERT_UNIT2453NEARESTDOWNIGNOREABORT?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?i?iB@iB@i?i?i?iR@iR@iR@iR@iR@iR@iR@iR@iR@iB@iB@i?i?i?i?i?i?i2@i?i?i?i?i?i?i?i?i?i"@i?i@i?i?i?i?i@i?i?i?i?i?i?i?i?i?i?i?i?i?i?i2@i?i?i?i?i?i?i?i?i?i"@i?i@i?i?i?i?i@i{x|xo||x{x |x[x|x|xFortran runtime warning: IEEE 'denormal number' exception not supported. 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E,W8 9qIHۚ풴lMP#*wg:8-ñj@?F[$GtJL0s-o|;#o`Is{Kҵ65m1 k?f%(炸r;v=4tPw?j&ATN4 @SZ E3TɤAc+;={CpfU,ie.O\Oߢݭ9^2XX%-VNqv4§v=ЉMOT+}\ IA?7߻D!WDGn®8pp;3,f%k;ܑyٸZNh.ltH Ic/~=otgx!RJݼ-ݎW5YAV9 T<!{>;b.w_ W5ƶ(NT ]=!̇odI@BuhؖҋcU4ph{3'"2I%% dKE)0b 62 kg SP)E7J G |l'5$5lPelglopopbllllllcl@oll{l`ll`lpllPel`lopopbllllllcl@oll{lpll`lpllPel_lopopbllllllcl@oll{l`ll`lplPl0tllРlllllllll@lPl ll0l`lplLIBC_FATAL_STDERR_/dev/tty======= Backtrace: ========= ======= Memory map: ======== /proc/self/maps,ccs=lllРll@lllllloll{l`ll`lpllllРll@llpzlll{loll{lpll`lplll}lРll@l}lp{lllloll{l`ll`lplPl0llРlllllllll@lPl ll0l`lplcorrupted double-linked listmalloc: top chunk is corruptmalloc: using debugging hooksTOP_PAD_PERTURB_MMAP_MAX_ARENA_MAXARENA_TESTPER_THREADTRIM_THRESHOLD_MMAP_THRESHOLD_Arena %d: system bytes = %10u in use bytes = %10u Total (incl. mmap): max mmap regions = %10u max mmap bytes = %10lu free(): invalid pointerfree(): invalid sizemalloc(): memory corruptionrealloc(): invalid pointerrealloc(): invalid next sizerealloc(): invalid old size*** glibc detected *** %s: %s: 0x%s *** double free or corruption (!prev)free(): invalid next size (normal)free(): invalid next size (fast)double free or corruption (fasttop)double free or corruption (top)double free or corruption (out)free(): corrupted unsorted chunksmunmap_chunk(): invalid pointermalloc(): memory corruption (fast)malloc(): smallbin double linked list corruptedmalloc(): corrupted unsorted chunksmalloc(): corrupted unsorted chunks 2break adjusted to free malloc space~lfllllflflflfllRlll"llllllglUnknown errorUnknown error YmZYmYmJZmZmZmZ[m[mYmVYmYmFZmZmZmV[m[mYmRYmYmBZmZmZmR[m[mYmNYmYm>ZmZmZmN[m[mYmJYmYm:ZmZmZmJ[m[mYmFYmYm6ZmZmZmF[m[mYmBYmYm2ZmZmZmB[m[mYm>YmYm.ZmZmZm>[m[mYm:YmYm*ZmZmZm:[m[mYm6YmYm&ZmZmZm6[m[mYm2YmYm"ZmZmZm2[m[mYm.YmYmZm~ZmZm.[m[m~Ym*YmYmZmzZmZm*[m[mzYm&YmYmZmvZmZm&[m[mvYm"YmYmZmrZmZm"[m[mrYmYmYmZmnZmZm[m~[mnYmYmYmZmgZmZm[mw[mgYmYmYmZm`ZmZm[mp[m`Ym\m \mC\m@\mS\mP\ms\mp\m\m\m3\m0\m\m\mc\m`\mE^m^m^m_mc_m_m_m?`m`m`m amlamambmTbmbm@^m^m^m_m^_m_m_m:`m`m`mamgamambmObmbm;^m^m^m_mY_m_m_m5`m`m`mambamamamJbmbm6^mz^m^m _mT_m_m_m0`m~`m`mam]amamamEbmbm1^mu^m^m_mO_m_m_m+`my`m`m amXamamam@bmbm,^mp^m^m^mJ_m_m_m&`mt`m`mamSamamam;bmbm'^mk^m^m^mE_m_m_m!`mo`m`mamNamamam6bmbm"^mf^m^m^m@_m_m_m`mj`m`m`mIamamam1bmbm^m^^m^m^m8_m_m_m`mb`m`m`mAamamam)bmxbm^mV^m^m^m0_mw_m_m `mZ`m`m`m9amamam!bmpbm ^mN^m^m^m(_mo_m_m`mR`m`m`m1amamambmhbm^mF^m^m^m _mg_m_m_mJ`m`m`m)amxamambm`bmnm#nmnmnmnmnmnmnmpm-qmqmqmpmpmpmpmvmvmvmvmvmvm1wmwm!wmGwmGwmGwmfvmGwmfvmpwmfvmwwmfvm~wmwmwmwmwmwmOwmOwmOwmfvmOwmfvmpwmfvmwwmfvm~wmwmwmwmwmWwm  @   @ @@!@"@#@% @)@@,@0@9@:@;@<@=@>@?@A B C D E  F@@G@H0 @I@@J` @K@L @M@N`@`@@f @g@@h@x@y@z@{@|@} @@    @@@@ @@ @@@ @@ @ @ @@@@@ @@ANSI_X3.4-1968//TRANSLIT`{{ {${`$nn${ {nTZ/etc/localtimeUniversalUTC%[^0-9,+-]%hu:%hu:%huM%hu.%hu.%hu%nGMT../TZDIRTZifposixrules/usr/share/zoneinfoGETCONF_DIR/usr/libexec/getconf/proc/sys/kernel/ngroups_maxILP32_OFF32ILP32_OFFBIG/proc/sys/kernel/rtsig-maxmmUm}mom9mmmm:m:m:m:m:m:m:m:m:m:m:m:m:m:mmm/m'mmm:mmEmmmmmߪm5mߪmժmom`mEm5mm5m:m:m:mmm:m:mmmmmmmmmmmmmmm:m:mmmmEmmmmm:m:m:m:m:m:m mmm߫m'mիmɫmmmmmm:mmmmmm[m%mm'mOmemEm9m/mm%mmmŪmomemmIm?m5m'm'm'm'mmmmmmmm:m:mmmm:mmmmmmmmmmmmmmmm:m:mmmmm:mmmmm:mmmmmmmmmmmmmmmmemmmmmymymymymymymymymymymymymymym`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m`m:m:mstdinstdoutstderr/dev/pts/devsyslog: unknown facility/priority: %x<%d>%h %e %T [%d]/dev/console%s /proc/meminfoMemFree: %ld kBMemTotal: %ld kB/proc/stat/proc/cpuinfoprocessor/sys/devices/system/cpu+0x-0x[0x*** stack smashing detected ***: %s terminated 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RsEURa/ca/sCc/oc/ugHHHhIILlNNoPQRRRTEL(TM)ZOhmZBCeeEFMoiDdeij 1/3 2/3 1/5 2/5 3/5 4/5 1/6 5/6 1/8 3/8 5/8 7/8 1/IIIIIIIVVVIVIIVIIIIXXXIXIILCDMiiiiiiivvviviiviiiixxxixiilcdm<--><-><==><=>-/\*|:~<=>=<<>><<<>>>NULSOHSTXETXEOTENQACKBELBSHTLFVTFFCRSOSIDLEDC1DC2DC3DC4NAKSYNETBCANEMSUBESCFSGSRSUSSPDEL_NL(1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(1)(2)(3)(4)(5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)1.2.3.4.5.6.7.8.9.10.11.12.13.14.15.16.17.18.19.20.(a)(b)(c)(d)(e)(f)(g)(h)(i)(j)(k)(l)(m)(n)(o)(p)(q)(r)(s)(t)(u)(v)(w)(x)(y)(z)(A)(B)(C)(D)(E)(F)(G)(H)(I)(J)(K)(L)(M)(N)(O)(P)(Q)(R)(S)(T)(U)(V)(W)(X)(Y)(Z)(a)(b)(c)(d)(e)(f)(g)(h)(i)(j)(k)(l)(m)(n)(o)(p)(q)(r)(s)(t)(u)(v)(w)(x)(y)(z)(0)-|+++++++++o::====== =(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47)(48)(49)(50)hPadaAUbaroVpcpAnAuAmAkAKBMBGBcalkcalpFnFuFugmgkgHzkHzMHzGHzTHzulmldlklfmnmummmcmkmmm^2cm^2m^2km^2mm^3cm^3m^3km^3m/sm/s^2PakPaMPaGParadrad/srad/s^2psnsusmspVnVuVmVkVMVpWnWuWmWkWMWa.m.BqcccdC/kgCo.dBGyhaHPinKKKMktlmlnloglxmbmilmolPHp.m.PPMPRsrSvWbfffiflffifflst+___,.;:?!(){}#&*+-<>=\$%@!"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZabcdefgijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyzACDGJKNOPQSTUVWXYZabcdfhijkmnpqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyzABDEFGJKLMNOPQSTUVWXYabcdefghijklmnopqrstuvwxyzABDEFGIJKLMOSTUVWXYabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz01234567890123456789012345678901234567890123456789679023456789?libcANSI_X3.4-1968@|} }}}}}@}}}@}@}|| |f{f{f{f{f{f{f{f{f{f{f{f{f{$I$I$88.袋.NNN$I$I$88_Cy 5aa.袋.B,dGzGNNN_B{ %$I$I$a{B!B>880123456789abcdefghijklmnopqrstuvwxyz0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZto_outpunct(nil)(null)*** %n in writable segment detected *** *** invalid %N$ use detected *** PnPnPnPnPnPnPnPnPnPnPnPnPnPn nxnnnnnnnn\nҽn$nnPnPnPnnnnnnnnnnnnnnnnٿnnooooooooooooooVooJooVoVoVooooooopoo|oooooooooooooooooooooooooooooooooooooooooooooooooooڤooooooooooooooooooooooooooooooooǤoooooڤoooooooooo/oo oo/o/o/ooooooooooooooooomooooooooo/oo#omo/o/o/oomoooooIomoUoooaoomooomo 0000000000000000 0000000000000000`ooo@opo`oo]n@o0llРlllllllol@lPl ll0l`lpl???%.3s %.3s%3d %.2d:%.2d:%.2d %d ;Zx0Nm<[y1On%H:%M%H:%M:%S%m/%d/%y%Y-%m-%d%I:%M:%S %po!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!oo!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!o!ooooo!oopoo!o!o!op!o!op!op$pp ppJpppp!o!o!o!o!o!opoHpmpp!opo!oooWouoo!oo!oooo:p!opzpp*pcannot create cache for search pathELF file data encoding not little-endianELF file version ident does not match current oneELF file version does not match current oneonly ET_DYN and ET_EXEC can be loadedELF file's phentsize not the expected sizefile=%s [%lu]; generating link map cannot create shared object descriptorELF load command address/offset not properly alignedELF load command past end of fileobject file has no loadable segmentscannot dynamically load executablecannot change memory protectionsELF load command alignment not page-alignedcannot allocate TLS data structures for initial threadfailed to map segment from shared objectobject file has no dynamic sectionshared object cannot be dlopen()edcannot allocate memory for program headercannot enable executable stack as shared object requires dynamic: 0x%0*lx base: 0x%0*lx size: 0x%0*Zx entry: 0x%0*lx phdr: 0x%0*lx phnum: %*u cannot create search path arraycannot create RUNPATH/RPATH copy file=%s [%lu]; needed by %s [%lu] find library=%s [%lu]; searching cannot open shared object filecannot allocate name record search path=:%s (%s from file %s) (%s) file too shortcannot read file datainvalid ELF headerELF file OS ABI invalidELF file ABI version invalidinternal error trying file=%s cannot stat shared objectcannot map zero-fill pagescannot close file descriptorsystem search path:;ORIGINPLATFORMLIBlib64RPATHRUNPATHwrong ELF class: ELFCLASS32/lib64//usr/lib64/ GNUELF/etc/ld.so.cache search cache=%s ld.so-1.7.0glibc-ld.so.cache1.1symbol=%s; lookup in file=%s [%lu] file=%s [%lu]; needed by %s [%lu] (relocation dependency) binding file %s [%lu] to %s [%lu]: %s symbol `%s' (no version symbols)symbol , version not defined in file with link time reference

relocation errorsymbol lookup errorprotectednormal [%s] undefined symbol: cannot allocate memory in static TLS blockcannot make segment writable for relocation%s: Symbol `%s' causes overflow in R_X86_64_32 relocation %s: Symbol `%s' causes overflow in R_X86_64_PC32 relocation %s: Symbol `%s' has different size in shared object, consider re-linking %s: no PLTREL found in object %s %s: out of memory to store relocation results for %s cannot restore segment prot after reloc (lazy) relocation processing: %s%s |p7}p7p|p|p|p7}p7}p|p|pp|p|p|p|p|pppOp~ppp~p~p~ppp~p~pp~p~p~p~p~pppFpunexpected reloc type 0xunexpected PLT reloc type 0xcannot apply additional memory protection after relocationDYNAMIC LINKER BUG!!!%s: %s: %s%s%s%s%s continuedfatal%s: error: %s: %s (%s) out of memoryerror while loading shared librariescannot create TLS data structuresdlopen/proc/self/exeGLIBC_PRIVATE_dl_open_hook^[yY]^[nN]f{\}b}'}'}m|f{.'}'}'}'}'}'}'}}}}}}}}}p{}}}}}}'}'}}}}}}}}}}}}}}}u'u'm|f{rx'}'}.m|SunMonTueWedThuFriSatSundayMondayTuesdayWednesdayThursdayFridaySaturdayJanFebMarAprMayJunJulAugSepOctNovDecJanuaryFebruaryMarchAprilJuneJulyAugustSeptemberOctoberNovemberDecemberAMPM%a %b %e %H:%M:%S %Y%a %b %e %H:%M:%S %Z %YSunMonTueWedThuFriSatSundayMondayFridayJanFebMarAprMayJunJulAugSepOctNovDecMarchAprilJuneJulyAugustAMPMTuesdayWednesdayThursdaySaturdayJanuaryFebruarySeptemberOctoberNovemberDecember%a %b %e %H:%M:%S %Y%m/%d/%y%H:%M:%S%I:%M:%S %p%a %b %e %H:%M:%S %Z %Yf{o0}4}8}<}@}D}H}L}S}Z}b}l}u}|}}}}}}}}}}}}}}}}}}}}}}}}}} } }c|Z|u|'}'}'}'}'}'}'}@}P}`}p}}}}}}P }p } }} }}}$}4}D}T}d}t}}}}} } }}}D}} } }0 }X }x } }8 }D } } }H }p }@|@|@|@|@|"}:0$}"}&}&}'}(} }m|f{)m|%p%t%g%t%m%t%ff{}'}'}'}'}'}m|%a%N%f%N%d%N%b%N%s %h %e %r%N%C-%z %T%N%c%Nf{ }'}'}'}'}'}'}'}'}'}'}'}m|+%c %a %lf{}'}'}'}m|f{&}m|ISO/IEC 14652 i18n FDCC-setKeld Simonsenkeld@dkuug.dk+45 3122-6543+45 3325-6543ISO1.01997-12-20ISO/IEC JTC1/SC22/WG20 - internationalizationC/o Keld Simonsen, Skt. Jorgens Alle 8, DK-1615 Kobenhavn Vi18n:1999i18n:1999i18n:1999i18n:1999i18n:1999i18n:1999i18n:1999i18n:1999i18n:1999i18n:1999i18n:1999i18n:1999i18n:1999i18n:1999i18n:1999i18n:1999f{}}(}}}}}'}}'}'}'}}}}m|f{}}m|  !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~  !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz{|}~0123456789abcdefghijklmnopqrstuvwxyz0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZto_inpunctp~p~p~p~p~p~p~p~p~p~p~p~p~p~p~p~p~p~p~p~pp~p~p~p~p~p~pZp~pp~pwp~p~p~p~pp~p~pp~p~p~p~p~ppapppppppppppppppppppppppppppp@ppϲpp@p@p@ppppppppppppҳpppppWppp˺pppppp@pppp@p@p@ppNppppppfppppڼpp4pppWp_dlfcn_hook%s%s%s%s%s%s: %sunsupported dlinfo requestHqXqqHqqqqHqHqzqeqinvalid namespace%s: cannot open file: %s %s: cannot create file: %s %s: cannot map file: %s %s: cannot stat file: %s %s: file is no correct profile data file for `%s' Out of memory while initializing profiler invalid mode for dlopen()cannot extend global scopecannot create scope listno more namespaces available for dlmopen()invalid target namespace in dlmopen()opening file=%s [%lu]; direct_opencount=%u TLS generation counter wrapped! Please report this. closing file=%s; direct_opencount=%u file=%s [%lu]; destroying link map TLS generation counter wrapped! 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20080704 (Red Hat 4.1.2-55)GCC: (GNU) 4.1.2 20080704 (Red Hat 4.1.2-55)GCC: (GNU) 4.1.2 20080704 (Red Hat 4.1.2-55)GCC: (GNU) 4.1.2 20080704 (Red Hat 4.1.2-55)GCC: (GNU) 4.1.2 20080704 (Red Hat 4.1.2-55)GCC: (GNU) 4.1.2 20080704 (Red Hat 4.1.2-55)GCC: (GNU) 4.1.2 20080704 (Red Hat 4.1.2-55)GCC: (GNU) 4.1.2 20080704 (Red Hat 4.1.2-55)GCC: (GNU) 4.1.2 20080704 (Red Hat 4.1.2-55)GCC: (GNU) 4.1.2 20080704 (Red Hat 4.1.2-55)GCC: (GNU) 4.1.2 20080704 (Red Hat 4.1.2-55)GCC: (GNU) 4.1.2 20080704 (Red Hat 4.1.2-55)GCC: (GNU) 4.1.2 20080704 (Red Hat 4.1.2-55)GCC: (GNU) 4.1.2 20080704 (Red Hat 4.1.2-55)GCC: (GNU) 4.1.2 20080704 (Red Hat 4.1.2-55)GCC: (GNU) 4.1.2 20080704 (Red Hat 4.1.2-55)GCC: (GNU) 4.1.2 20080704 (Red Hat 4.1.2-55)GCC: (GNU) 4.1.2 20080704 (Red Hat 4.1.2-55)>stapsdty)pp+}libcrtld_map_complete-8@%r15 8@%rbxEstapsdt=7pp+}libcrtld_map_start-8@32(%rbp) 8@-240(%rbp)Fstapsdt9'qp+}libcrtld_map_complete-8@40(%r15) 8@16(%rsp)Estapsdt'qp+}libcrtld_reloc_start-8@40(%r15) 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